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WHAT TAKEOUT CAN TEACH US ABOUT CX

WHY CCM PROJECTS GO SIDEWAYS BEFORE YOU MOVE TO SaaS

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FROM OBLIGATION TO

OPPORTUNITY It’s time to turn statements, notices and disclosures into better customer experiences

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TABLE OF CONTENTS

FALL 2026

FEATURES

From Obligation to Opportunity — Compliance to Connection Why financial services organizations need to rethink mandatory customer communications as part of the customer experience By Andy Keller

Why CCM Projects Go Sideways The hidden complexity behind migration overruns — and how to build a more realistic path forward By Jennifer Raml

Before You Move to SaaS The communications strategy work that determines whether your SaaS migration succeeds By Bryan Matlock

Status-as-a-Service

What highly regulated industries can learn from your last takeout order By Scott Draeger

AI & INTELLIGENT AUTOMATION

By Eric Riz

What CCM and CXM leaders need to know By Liz Stephen & Mia Papanicolaou

VERTICAL FOCUS — HEALTHCARE & UTILITIES

Content Compliance By Design

Embedding accessibility and privacy from day one

Generative AI vs. Agentic AI

The AI-CX Connection Why utilities must solve their data, integration and governance challenges before AI can deliver a better customer experience By John Harney

Building Trust into Every Healthcare Communication How security, accessibility and omnichannel delivery shape the health plan member experience By Jason Pothen

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The Hidden Cost of Communication Complexity: Why Regulated Industries Must Rethink Content Management

DEPARTMENTS

06 07 4

Letter from the Advisory Board What’s New

fall.2026 DOCUMENTmedia.com

What the Analysts Say

LETTER FROM THE ADVISORY BOARD:

president Chad Griepentrog publisher Ken Waddell

CCM at a Crossroads

By Andy Keller

managing editor Erin Eagan [ erin@rbpub.com ] contributing editor Amanda Armendariz contributors Scott Draeger John Harney Andy Keller Bryan Matlock Mia Papanicolaou Jason Pothen Jennifer Raml Eric Riz Elizabeth Stephen advertising Ken Waddell [ ken.w@rbpub.com ] 608.235.2212 audience development manager Rachel Chapman [ rachel@rbpub.com ] creative director Kelli Cooke

Customer communications are at an important crossroads. Technology is evolving rapidly, customer expectations continue to rise and regulatory requirements are becoming more complex. Yet one thing remains clear: there is no magic-bullet solution for Customer Communications Management (CCM). Successful transformation requires the right combination of people, processes, content, data, technology, governance and strategy. This issue explores the challenges and opportunities facing CCM and CXM today. We begin by examining why CCM projects are difficult and why technology alone cannot solve the underlying challenges. We then look at what highly regulated industries can learn from the real-time visibility customers have come to expect from everyday experiences like ordering takeout. For organizations moving from on-premises CCM to SaaS, we explore what changes, what remains the same and why communications strategy must remain at the center of the trans6

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formation. We also challenge organizations to rethink required messaging in “From Obligation to Opportunity,” demonstrating how every statement, notice or bill is a vital customer touchpoint and a chance to build trust. No discussion of the future would be complete without AI. Our exploration of Generative AI versus Agentic AI examines what leaders need to understand as these technologies reshape how communications are created, managed and delivered. That opportunity, however, must be grounded in responsibility. “Content Compliance by Design” explores embedding accessibility and privacy into communications from day one, rather than treating them as afterthoughts. Finally, our healthcare and utilities focus demonstrates how these principles apply in industries where clear, timely and trusted communications can have an especially significant impact. The future of CCM is not simply about adopting new technology. It is about using technology, strategy, and customer insight together to create better experiences. We invite you to explore this issue and consider how your organization can turn every communication into an opportunity.

PO BOX 259098 Madison WI 53725-9098 p: 608-241-8777 f: 608-241-8666 email: customerservice@rbpub.com DOCUMENT Strategy Media (ISSN 1081-4078) is published on a daily basis via its online portal and produces special print editions by Madmen3, PO BOX 259098, Madison, WI 53725-9098. All material in this magazine is copyrighted ©2026 by Madmen3 All rights reserved. Nothing may be reproduced in whole or in part without written permission from the publisher. Any correspondence sent to DOCUMENT Strategy Media, Madmen3, or its staff becomes the property of Madmen3. The articles in this magazine represent the views of the authors and not those of Madmen3 or DOCUMENT Strategy Media. Madmen3 and/or DOCUMENT Strategy Media expressly disclaim any liability for the products or services sold or otherwise endorsed by advertisers or authors included in this magazine. SUBSCRIPTIONS: DOCUMENT Strategy Media is the essential publication for executives, directors, and managers involved in the core areas of Communications, Enterprise Content Management, and Information Management strategies. Free to qualified recipients; subscribe at documentmedia.com/subscribe. REPRINTS: For high quality reprints, please contact Chad Griepentrog, 608-241-8777, chad.g@rbpub.com

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What’s New Catch up on all the news, opinions, and current events happening around the industry.

When AI Writes to the Patient: Healthcare Communications Face New Rules

Myriad Genetics Rethinks AI Document Processing — and Cuts Processing from Minutes to Seconds Myriad Genetics reportedly rebuilt an internal AI document-processing system used for diagnostic, insurance and reimbursement operations after its first version was too expensive and didn’t perform well enough. The new system reduced document-processing time from about 10 minutes to roughly 20 seconds and, by early 2026, was saving approximately 300 staff hours per month while handling around 9,000 prior authorizations in its women’s health operation.

States are increasingly regulating how AI can be used in healthcare, including requirements to disclose when AI is involved in patient communications. California’s AB 3030, for example, requires certain healthcare providers to include a disclaimer when generative AI creates patient communications containing clinical information, along with instructions for contacting a human provider. A recent August regulatory overview points to patient transparency and disclosure as one of the major areas organizations now have to navigate.

DOCUMENTmedia.com fall.2026

By Andy Keller

FROM OBLIGATION TO OPPORTUNITY — COMPLIANCE TO CONNECTION

Why financial services organizations need to rethink mandatory customer communications as part of the customer experience 8

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SUBSCRIBE FOR FREE! and, more recently, experimenting with AI-driven personalization. Yet many of these high-stakes customer interactions are still governed by content, systems and processes designed for another era. This must change. Every message a financial services company sends is an interaction with a customer. It can build confidence, reinforce loyalty and demonstrate that the organization understands what the customer needs. Poor experience can create confusion, frustration and distrust. After 42 years in banking and insurance communication, including time as the Operational Messaging Architect at USAA, I have watched enterprise messaging evolve from paper to omnichannel. Yet, real effectiveness remains elusive. Mandatory communications should be useful, understandable experiences that strengthen the customer relationship. Too often, organizations treat these touches as a compliance obligation rather than a strategic opportunity which leads to underinvestment in the moments where customer attention is highest. The difference is rarely technology alone. It is the recognition that customer communications are not simply documents. They are experiences.

Your Bill Is Your Brand

aking Every Customer Message Matter

Customers do not separate a company’s communications from their overall experience with the company.  Your bill is your brand.  Your claim letter is your customer experience.  Your outage notification is your reputation.  Your renewal notice is your retention strategy.

In financial services, communication is often treated as a necessary obligation. A policy document must be delivered, an account statement must be sent, a claim letter must go out and a renewal notice must arrive on time. These communications are essential, but they are rarely viewed as part of the customer experience. At the same time, financial institutions have spent years modernizing channels, adding digital capabilities

For the customer, these distinctions are irrelevant. They don’t see the organizational structure behind the message. They don’t know which department created it, which legacy platform generated it or which vendor printed and mailed it. They simply see a message from their financial services company. That makes every communication a moment of truth. Unfortunately, many of the communications customers receive today were never designed for the expectations

of modern consumers. They were built primarily for compliance, developed in organizational silos, designed around print-first delivery and structured around products rather than people. As a result, they can be difficult to personalize, difficult to change and difficult to deliver consistently across channels. The result is a paradox: organizations may have invested enormously in digital transformation while still communicating with customers using processes and content designed for another era.

The Hidden Cost of Poor Communication Poor communication has consequences that extend well beyond an unattractive document or an awkward digital experience. For a business it can mean lower digital adoption, reduced trust and higher customer churn. For customers, the experience can produce confusion, frustration, anxiety and the feeling that the organization simply isn’t listening. Consider a customer receiving a renewal notice that is technically correct but difficult to understand. The organization may consider the communication successful because it meets every regulatory requirement. The customer may experience it very differently. If the customer cannot quickly determine what is changing, what action is required or why the change matters, the communication has failed at a fundamental level, even if it has passed every compliance review. This is where the industry needs to move beyond the checkbox. Compliance is essential. But compliance should be the floor, not the ceiling. The question should not simply be, “Did we send the required information?” It should be, “Did we communicate in a way that helped the customer understand what they need to know and what they need to do?”

Why Modernization Is So Difficult If the answer seems obvious, why is meaningful modernization so difficult? Part of the problem is technology. Many financial service organizations still depend on legacy platforms and proprietary systems that were designed around previous generations of business DOCUMENTmedia.com fall.2026

requirements. Replacing those systems is expensive, risky and disruptive. But technology is only one part of the challenge. Organizational structures can be equally problematic. Communication ownership is often decentralized, with different departments responsible for different pieces of the customer journey. Without strong governance, communications can become inconsistent in tone, content, design and delivery. Then there is the cultural challenge. Organizations that have spent decades prioritizing regulatory compliance understandably develop a culture of caution. People become reluctant to change communications that have “always worked.” They worry about disrupting established processes or inadvertently creating regulatory problems. Those concerns are legitimate. But they can also become barriers to improvement. Modernization does not mean abandoning compliance. It means designing compliance into a better customer experience.

What Good Looks Like So, what should modern customer communication feel like? It should be:  Relevant  Timely  Consistent  Personalized  Human  Clear  Trusted Those characteristics may sound simple but achieving them at enterprise scale requires a fundamentally different approach to communications. Relevance means giving customers information that matters to their situation rather than forcing them to interpret generic messages. Timeliness means delivering information when it is most useful, not simply when an internal process happens to generate it. Consistency means ensuring that the customer receives the same essential message regardless of whether they interact through print, email, a website, a mobile application or another channel. 10

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Personalization means going beyond inserting a customer’s name. It means understanding the customer’s context and using that understanding to make communication more useful. And being human means recognizing that communication often arrives at important moments in people’s lives. A claim, a rate increase, a policy change or a cancellation notice can carry significant emotional weight. The technology may be digital. The customer is human.

Moving a confusing paper letter into a PDF does not make the communication better. Five Foundations for Modernization Building this kind of communication capability requires more than redesigning documents. Five foundations are particularly important.  Establish an enterprise content strategy  Pursue channel independence  Develop a migration strategy  Secure executive sponsorship  Measure understanding and outcomes An enterprise content strategy allows organizations to understand their communications as a connected ecosystem rather than a collection of independent documents. Channel independence means content should not be trapped inside a particular delivery channel. Organizations should be able to manage the message independently whether it ultimately reaches the customer through print, email, web or another channel. A migration strategy concedes that modernization rarely happens overnight. Legacy systems and processes need to coexist with new capabilities during a transition. A thoughtful migration strategy reduces risk while creating a path toward the future.

Executive sponsorship is essential because communication modernization crosses technology, operations, compliance, marketing and customer experience. Without leadership support, efforts can become fragmented or stall when competing priorities emerge. Measure understanding and outcomes. Organizations need to understand whether communications are improving customer behavior and experience. Measurement turns communication from an operational expense into something that can be managed as a strategic business capability.

Turning Obligations into Opportunities Perhaps the most important mindset shift is to stop thinking of required communications as burdens. Every required communication is an opportunity. It is an opportunity to build trust, reduce friction, strengthen loyalty, encourage digital engagement and reinforce brand values. A financial services company cannot choose whether it needs to send certain regulatory or contractual communications. But it can choose how those communications make customers feel. That distinction matters. The customer may never remember the exact language of a renewal notice. They may, however, remember whether the company made the process easy or difficult. They may not remember the precise wording of a claim letter. They will remember whether they felt informed, respected and supported during a stressful moment. This is where empathy becomes a competitive advantage.

AI Can Help—But It Is Not the Answer by Itself Artificial intelligence will accelerate the transformation of customer communications. AI creates opportunities for personalization at scale, sentiment-aware messaging, intelligent channel selection and predictive communication strategies. But there is an important caveat: AI cannot compensate for poor foundations.

SUBSCRIBE FOR FREE! Effective AI-driven communication requires clean content, structured data and strong governance. An organization cannot simply place artificial intelligence on top of fragmented content, inconsistent data and disconnected processes and expect meaningful results. In fact, AI may make those weaknesses more visible. The organizations best positioned to take advantage of AI will be those that have already begun treating content, data, governance and customer communications as strategic assets. AI can help organizations communicate more intelligently. It cannot decide what a company should stand for. This remains a human responsibility.

The Future Is Digital and Human The financial services industry has made enormous progress in digitizing customer interactions. But digital transformation should not be confused with customer-centric transformation. Moving a confusing paper letter into a PDF does not make the

communication better. Putting the same content into an email does not automatically make it digital-first. True modernization requires organizations to rethink the purpose of communication itself. Customers remember how communications make them feel. And modernization is no longer optional. Compliance is mandatory. Empathy is differentiating. The organizations that succeed will be those that recognize every communication as part of the customer relationship. They will design messages around people rather than products. They will use technology to remove friction rather than simply automate existing processes. They will measure communications based not only on whether they were delivered, but on whether they were understood and useful. Finally, they will recognize that the most sophisticated communication platform in the world is ultimately serving a very simple purpose: helping one person understand what an organization is trying to tell them.

The future of customer communications is not just digital. It’s human.

ANDY KELLER is an industry consultant specializing in Customer Communication Management (CCM), with more than four decades of experience in communications technology, document management, and omnichannel customer communications. Andy began his career at USAA in 1984 and retired after 42 years with the organization. His areas of expertise include Customer Communication Management, eDelivery, Document Accessibility, and print vendor management. He also maintains a broad understanding of Document Archive and Records Management. Andy has shared his knowledge and industry perspective through the Document Strategy Forum, where he served as an Advisory Board Member, as well as through other industry organizations and forums. Today, Andy brings his 42 years of experience to his work as an independent industry consultant, helping organizations navigate the evolving CCM landscape and develop effective, accessible, and customer-focused communication strategies.

DOCUMENTmedia.com fall.2026

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and more decisions made under compressed timelines. If your project is running long, over budget, or fighting data-quality gremlins, you are inside the industry norm.

WHY CCM PROJECTS GO SIDEWAYS

The hidden complexity behind migration overruns — and how to build a more realistic path forward

By Jennifer Raml

f you’re staring at a Gantt chart that’s slipped three quarters, a budget that’s doubled, or a migration that looked simple in the demo and turned into a two-year saga, take a breath. You are far from alone. This post is for everyone doing the work in Customer Communications Management. Developers wrangling templates, architects making the case for architectural discipline, operations leads nursing print streams through overnight runs, project managers translating between vendors and reality, directors keeping it all funded, and executives seeing the gap between the original business case and the reality of the work. The Numbers Say What You’re Feeling This isn’t just a bad mood. It’s an industry pattern backed by hard evidence:  Bloor Research has tracked data migrations for two decades and 14

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consistently finds that roughly 84% either fail to meet objectives or significantly overrun time and budget.  Gartner has published multiple studies showing cloud and data migration overruns of 30 to 50% are common, with more than 60% of organizations exceeding their initial migration budget.  Industry research consistently finds organizations spend roughly a third of migration budgets correcting data quality problems that weren’t properly scoped upfront.  Panorama Consulting’s 2024 ERP Report found 72% of ERP projects exceeded their original budget, with an average overrun of 24%, and CCM migrations ride on similar data foundations.  The CCM market itself is projected to grow from $2.3B in 2025 to roughly $5.3B by 2032 according to industry market research, meaning more options

CCM Is Genuinely Hard There’s a quiet shame around struggling CCM projects. Teams assume that because the demo looked easy, the work should be easy. When it isn’t, they blame themselves. The difficulty is not your fault. It’s the nature of the work. CCM sits at the intersection of forces that would each, individually, be a serious engineering challenge: decades of regulatory requirements baked into templates by people long retired; high-volume print operations spanning AFP, PostScript, PCL, IPDS, MICR, postal optimization, and inserter control; complex data integration across mainframes, policy admin systems, claims platforms, CRMs, and data warehouses; multi-channel orchestration across print, email, SMS, push, portal, and archive; accessibility and compliance obligations; customer experience expectations set by consumer tech giants; and now AI governance, adding model selection, hallucination controls, bias monitoring, and audit trails. Any one of these is a career’s worth of expertise. CCM professionals navigate all of them at once. If it feels heavy, that’s because it is heavy. Why Projects Go Sideways Most struggling CCM projects share an origin story. A team saw a polished demo of a modern, cloud-native, AI-powered platform. The pitch emphasized speed, simplicity, and lower cost. The current platform looked older and more expensive by comparison. A decision got made, sometimes before the technical team was fully engaged. The demo templates were simple, and yours aren’t. Low-code tooling struggles with 20 years of accumulated conditional logic. The new platform doesn’t natively handle every corner of your AFP archive or mainframe feed. Migration tooling handles the straightforward majority and leaves harder edge

SUBSCRIBE FOR FREE! cases to rebuild by hand. Integrations that took years to stabilize must be redone. AI features need governance frameworks before they touch regulated content. And even the best vendor services teams need time to understand why your existing templates were built the way they were, because that context lives in your organization, not theirs. None of this means the new platform was the wrong choice. It often means the transition was scoped for the demo, not for the reality underneath it. Meanwhile, you’re running two platforms in parallel, paying for both, while the business asks why this is taking so long. It’s happening at insurance carriers, banks, utilities, healthcare payers, and government agencies all over the world. There Is No Magic Platform There is no CCM platform that does it all perfectly. The work is too varied, too regulated, and too deeply wired into each organization for any single tool to cover every corner. What looks like bloat in a mature platform is usually the accumulated weight of real problems the platform learned to solve. Newer platforms have genuine strengths, and switching is sometimes the right call. But it should be made with eyes wide open, technical teams empowered, and realistic expectations on both sides of the table. Organizations can end up reverting, running both platforms indefinitely, or sitting half-migrated for years, not because their vendor was bad, but because the scope of the work was underestimated. Buying Well  Recognize the pattern before you sign. If a proposal implies your project will be an exception to the 84% overrun rate Bloor Research documented, ask in writing what specifically about your environment makes it easier than average.  Request the demo on your data. Your ten hardest documents, your real data feeds, your actual disclosures.  Put technical voices on the scoring committee. Not veto power, but

real scoring weight. Reward the people who raise hard questions.  Understand your advisors’ incentives. Ask directly whether they take referral fees, resale margins, or implementation revenue from any vendor you might select. Both models can be valuable; you just want to know which one you’re working with.  Analyze a 5-to-7-year Total Cost of Ownership (TCO). Include licenses, migration, integration rebuilds, training, parallel operations, decommissioning, AI governance, and 30 to 50% contingency.  Phase commitments. Pilot, prove, then expand. A vendor confident in their fit will usually welcome a phased structure because it builds trust on both sides.  Build exit ramps into every contract. Data portability, template export in usable formats, performance guarantees with remedies.  Calibrate AI claims carefully. AI is delivering real value in CCM today, but if a pitch implies AI will eliminate the need for your technical team, dig deeper into the claims.  Think in capabilities, not projects. Ask yourself, what will our organization be able to do after this project that we couldn’t do before, and will that ability still exist in five years? Building Well Make institutional knowledge visible by documenting the “why” behind templates, imperfectly but honestly. Get your hardest examples on the table early. If a platform can handle those, the easy ones follow. Translate concerns into business language: risk, cost, time, customer impact. Consider upgrading in place before replatforming, since many established platforms now have modern APIs and cloud options. Invest in data quality upfront. Build a cross-functional Center of Excellence that gives technical voices a permanent seat at the strategy table. Patience Is a Strategy Successful teams share a quiet, stubborn patience and discipline. They

make incremental progress, protect people from burnout, push back diplomatically against deadlines set before the work was fully understood, celebrate small wins, and build trust by being consistently honest, even when the news is hard. Before You Go The communications you help produce reach millions. They affect whether someone understands their medical bill, whether a policyholder knows their coverage, whether an accessibility-dependent reader can consume the same information as everyone else. That matters. The work is hard because the work matters. Be patient with yourself. Be honest with your leadership. Be realistic about what any single platform, old or new, can deliver. Build capability instead of chasing projects. Bring executives into the reality of the work, and technical people into the reality of the business. The gap between those two rooms is where most CCM projects lose their footing. Nearly every organization is working through some version of what you’re working through. The data proves it. They just don’t post about the hard parts on LinkedIn. You are not alone. You are not failing. You are doing one of the harder jobs in enterprise technology, and the fact that you care enough to do it well is already most of the battle.

JENNIFER RAML, CCM Application Development Manager at Symetra, is a strategic technology leader with over two decades of experience streamlining document workflows and customer communications in banking and insurance industries. She has successfully led enterprise-wide CCM implementations and automation initiatives while building high-performing technical teams. Her expertise spans document strategy, business analysis, and process optimization, with a proven track record in modernizing customer communications. In addition, Jennifer is a member of the DOCUMENT STRATEGY Advisory Board. DOCUMENTmedia.com fall.2026

BEFORE YOU MOVE TO SAAS The communications strategy work that determines whether your SaaS migration succeeds

BY BRYAN MATLOCK

fall.2026 DOCUMENTmedia.com

ost conversations about moving customer communications to SaaS start with the platform. The more useful conversation starts with the communications. A migration is one of the few moments when an organization has permission, budget and attention pointed at its communications at the same time. Spend that moment re-hosting what you already have and you inherit every problem you meant to leave behind. Spend it deliberately and you can close gaps that have been open for years. I work across platforms and processes for a living, and the pattern is

consistent: the teams that get real value from a SaaS move do the strategy work first and let the platform follow. Here is what I would put on the table before the migration, not after.

Start with an honest inventory, then rationalize it Most companies have multiple CCM systems that have mushroomed. Thousands of templates, dozens of near-duplicates and variations no one remembers creating. The instinct at migration time is to lift and shift all of it, because that feels safe and fast. However, it’s neither. You’re paying to move legacy complexity you should be decommissioning, and you’re importing

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it into a platform designed to let you generate new content even faster — multiplying the problem. Before you migrate, do an audit of what actually goes out, retire what does not and consolidate the rest into a governed set of shared components and reusable content fragments. The migration is your one clean chance to move a content model instead of a content mess.

Decide what the platform composes and what something else orchestrates SaaS communications platforms blur two jobs that deserve to stay distinct. One is composition: generating an accurate, compliant, well-designed document or message. The other is orchestration: deciding which message a customer gets, on which channel, at which moment, and how it connects to the last one. If you let the composition platform quietly own orchestration, you will re-platform again in two years when the customer experience outgrows it. Draw that boundary on purpose and let the CCM platform do what it is good at, then you can decide separately where journey logic and channel decisions will live.

Treat continuous updates as a governance change, not calendar change Having CCM on-premise means you control the pace. Upgrades are usually rare, planned and wrapped in a heavy regression test. SaaS reverses that, with features and fixes that arrive continuously and the model of the annual project and the big test cycle, cannot keep up. That is not a reason to slow the platform down, but it is a reason to redesign governance around it: lighter and continuous testing, real template versioning and an approval path that can move at the platform’s speed without losing legal and brand review.

Move from batch to events only where the business is ready

Much on-premise communication runs on but APIs and SaaS make real-time, event-driven communication possible, and it is genuinely better for the moments that matter: a confirmation the instant something happens, a status change while the customer is still paying attention. But real-time only helps when the upstream systems and the process behind them are ready to trigger cleanly. Pick the communications where immediacy changes the outcome, make those event-driven, and leave the rest on a schedule. Real-time everywhere is a cost, not a virtue.

A migration is your one clean chance to move a content model instead of a content mess. Make channel consistency and accessibility a condition of go-live The gap between print and digital, along with the accessibility gaps inside each, do not heal in the cloud, they simply migrate. The fix is to make consistency an acceptance criterion, not a later project: the same content, accurate across channels, accessible by design, tested against the standard you are held to. If a communication cannot meet that bar, it does not go live on the new platform. That turns the migration into the thing that finally closes the gap rather than the thing that preserves it.

Instrument for measurement while you have the platform open Most on-premise managed CCM platforms are very outdated and could tell you a document was produced and sent and very little after that. Modern platforms can emit real signals: delivered, opened, acted on, failed and why.

Decide the handful of measures that matter before you migrate and build the insight into the move. It is far cheaper to understand what measurement you need upfront rather than to bolt it on, and it is the difference between managing communications by anecdote and managing them by evidence.

Name the owners before the platform is live The most expensive words in this work are “no one is sure who owns the content.” A migration is the moment to fix that. Name an owner for the content model, an owner for governance, and an owner for the customer experience and keep those roles distinct from whoever owns the platform. Technology ownership and communications ownership are different jobs and the move is your reason to separate them cleanly.

Put the decisions in the right order None of this is an argument against SaaS. The move is usually right and the operating benefits are real. The argument is about sequence, so decide what you are trying to say to customers, through which channels, under what governance, and shape the content model that delivers it. Then choose the platform and deployment model that serve that strategy best, whether that is pure SaaS, on-premise, or the hybrid most enterprises actually land on. Do it in that order and the migration earns its keep. Do it in the other order and you will have paid for newer infrastructure and kept the same hard problems, now running faster.

BRYAN MATLOCK is a senior leader with a track record of building and leading high-performing sales and solutions engineering teams in the Commercial & Industrial Printing industry. He specializes in digital transformation strategies, enterprise communications processing, and customer experience management (CCM-CXM).

DOCUMENTmedia.com fall.2026

STATUS-AS-A-SERVICE What highly regulated industries can learn from your last takeout order

BY SCOTT DRAEGER

hink about the last time you ordered food through a delivery app. You watched the driver pick up your order, take a wrong turn, correct course and pull up at your front door. You knew exactly where your food was the entire time, and if something changed, you heard about it before you had to ask. Now think about the last time you submitted an insurance claim, applied for a loan or updated a healthcare plan. How much were you kept in the loop?

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That contrast gap has been widening for years. Consumers have been quietly trained by retail and entertainment to expect visibility as a default. Real-time tracking, instant confirmations and proactive updates when something changes are now the norm. None of it feels remarkable anymore because it has become the baseline of what good service looks like. The challenge is that regulated industries have not kept pace. The gap between what a customer experiences ordering dinner on a Saturday night

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and what they experience filing a claim on a Monday morning is real, measurable and increasingly difficult to justify.

The compliance checkbox problem Most customer communications in regulated industries were not designed around the customer. They were designed around the organization’s need for documentation. A form is submitted, an acknowledgement goes out, and weeks pass. Then, a decision arrives. From the organization’s perspective, the process worked. The right boxes were ticked and the right records were created. From the customer’s perspective, however, they were asked to wait in the dark with no idea how long a decision would take, or what to even expect next. Readers likely know where these gaps exist in their own organization’s journeys. They don’t know, however, what it’s costing them. According to Smart Communications’ 2026 benchmark report, unclear communications are the single most common reason consumers contact customer service instead of completing a process digitally — cited by 43% of respondents across all industries and age groups. Every one of those contacts is a call center interaction that didn’t need to happen, and at scale, that adds up to a significant and largely invisible operational cost that rarely gets traced back to the communication failure that caused it.

Status-as-a-Service What I am describing has a name that I think captures it well: Status-as-aService. The concept is that real-time progress updates, contextual guidance and continuous visibility are not premium features to be offered selectively. They are what a service experience should feel like as a baseline. This doesn’t mean flooding customers with notifications. Nobody wants that, and organizations that interpret proactive communication as

high-volume communication tend to make things worse rather than better. What it means is designing the experience so that the customer always knows where they are, what is happening, and what comes next — without having to initiate the conversation themselves. In practice, this looks like a claim tracker that explains not just which stage has been reached but what it means in plain terms, proactive updates when timelines shift, clearly signaling when AI is supporting a process and when a human adviser is involved, and systems that carry information forward so the customer is never asked to repeat themselves. Every time a customer has to re-explain their situation from scratch, they are absorbing friction that your organization created and they did not ask for.

Where implementation goes wrong The technology to make Status-as-aService work at scale exists today in a way it genuinely did not five years ago. But technology is not where most implementations fail. Where they fail is in treating automation as the goal rather than the means. Automation applied poorly does not close the gap between customer expectation and organizational delivery. It widens it. A stream of generic, templated status updates that arrive on schedule but say nothing meaningful can leave a customer feeling less informed than silence would. It makes customers feel like a case number, not a person. The distinction that matters is between designing communications that feel like conversations and designing communications that feel like broadcasts.

The business case Regulated industries are markets where products frequently look identical on the surface, like two insurers offering comparable cover or two banks offering similar rates. In those markets,

communication becomes a primary differentiator. Customers notice when it falls short, and they act on it. They switch providers, share their frustrations and become more receptive to competitors who promise something better. Our own research supports this: 63% of consumers say they are likely to switch away from a company if communications do not meet expectations. The organizations that treat communication as a cost center rather than a competitive asset tend to find that out when the churn numbers arrive and nobody can quite explain where the problem started.

Where to start For CCM leaders trying to figure out where Status-as-a-Service fits into an already full roadmap, the answer is not to start with the technology. Start with an honest audit of your current customer touchpoints. Not the version that looks good in a presentation, but the real one. Map the moments where the customer goes dark, where they submit something and hear nothing, and where they are expected to wait without knowing why. Then ask yourself one question: if this were happening to me, would I know what was going on? If the answer is no, you have found your starting point. The customer journey belongs to the customer, and the organizations that understand that are the ones building the kind of trust that holds when everything else looks the same.

SCOTT DRAEGER joined the customer communication industry by designing statements and marketing materials at an innovative service provider before joining the CCM industry. With over 20 years in CCM innovation, Scott has traveled the world to improve the way insurers, financial services organizations, health insurers, and other heavily regulated industries communicate authentically with their customers while complying with regulations.

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GENERATIVE AI VS. AGENTIC AI What CCM and CXM leaders need to know

By Mia Papanicolaou and Elizabeth Stephen

sk 10 vendors what they mean by AI in CCM and you will get 10 different answers, half of them describing generative AI and the other half describing agentic AI as though the two were interchangeable. For anyone responsible for composition, compliance or customer experience in a regulated industry, that blur is expensive. The difference between the two determines what you can safely automate, what still needs a human in the loop, where your next real gain in customer experience will come from and how exposed you are if you get the governance wrong. So it is worth being precise.

Generative AI Is a Faster Pen Generative AI produces content. Give it a prompt, a data set or a template and 20

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it will draft a letter, summarize a claim or suggest three subject lines for a renewal notice. In our work with health plan clients we have seen it used well to draft first-pass member communications, cutting the time a writer spends staring at a blank page. What it doesn’t do is make decisions because it doesn’t know that this member already called twice this month about a denied claim, that this account is flagged for a fraud review or that this customer switched channels last week and should probably not get another paper statement. It generates the words and a human or another system still has to decide when, whether and to whom. Across regulated industries this is already in production for firstpass drafting, summaries and variant generation, the high-volume work where a human still signs off, which is exactly where the value is showing up today.

Agentic AI Is a System That Acts Agentic AI does not just produce content, it takes action based on context and it can chain a series of decisions together to complete a goal without a person approving every step. In a CCM and CXM setting that means an agent could watch a customer’s journey in real time, recognize that a triggered communication is warranted, say a payment failure or a policy lapse, choose the right channel from that customer’s preference and past behavior, generate the content and route it, all inside a governed set of guardrails. This is the shift from proactive messaging to genuinely orchestrated, event-driven communication and it is where composition needs to head, away from batch-and-release platforms and toward systems that reason about the moment.

AI & INTELLIGENT AUTOMATION In Regulated Industries, the Distinction Is Not Academic Financial services, insurance, healthcare and utilities have spent two decades building a compliance skeleton around every communication that leaves the building, because a mistake in a customer letter can trigger a regulatory finding, not just an unhappy customer. Generative AI, used carelessly, erodes that discipline: a system inventing language on the fly, without the approval rigor you apply to a template, introduces a risk your compliance team may not know exists yet. Agentic AI raises the stakes again, because now the system is deciding and acting, not just drafting. An agent that chooses to send a payment reminder needs the same audit trail as the person who used to make that call by hand. Anything less is not innovation, it is exposure.

Name the Two Risks, and Govern By Design Stop calling everything your AI project. Content-generation risk is about what gets said and you govern it with tools you already know: approved language, review workflows and a human sign-off where the stakes justify it. Decisioning risk is about what gets done, to whom and when, and it needs a different set of controls such as guardrails on the actions an agent may take, suppression and eligibility rules it must respect and thresholds that force a human review. Whichever you are dealing with, build the governance in from the start rather than bolting it on after something breaks. Design it first and treat compliance as a constraint to build around, not a reason to wait.

Manage the Agent Like a Hire, and Instrument Everything An agent that acts on a customer’s behalf is, in effect, a member of your team and it should be managed like one, with an owner, a defined scope and someone accountable when it gets a decision wrong. The organizations that struggle are the ones that treated it as software to install rather than a role to onboard. The upside is

the audit trail since you can document every action an agent takes, what it saw, what it decided, why and what it did and you get a cleaner record than the manual process it replaced, because nothing depends on a person remembering to log it. Start where there is the lowest risk, a clear trigger and a narrow set of allowed actions, prove the governance there, then widen the scope.

Generative AI gave our industry a faster pen. Agentic AI is offering something bigger, a system that can notice what is happening to a customer and respond to it. Keep the Customer in View, and Buy for Governance None of this replaces the only question that matters, which is whether the customer is better off. A model that writes beautifully but sends the letter through a channel the customer abandoned years ago has improved nothing and an agent that acts in milliseconds but ignores the fact that this customer just spoke to a representative about the same issue has manufactured friction, not value. Ask whether the system can explain its choices, whether you can enforce guardrails it cannot override, whether it treats preference and consent as hard constraints, whether every action lands in an audit trail you control and whether it escalates to a human when it is unsure.

Where This Goes Next: Agentic Composition The next shift is not just an agent that decides and acts, it is one that

composes the communication itself. Most composition today is still batch and release, templates built in advance and sent on a schedule. Agentic composition moves that work to the moment: the system assembles the right document for this customer, in this situation, inside the same governed guardrails that decide when and whether it goes out. The generation and the decisioning stop being two separate systems: the pen that writes and the agent that acts become one motion, composing the right communication and choosing whether to send it in the same governed moment, under one audit trail. That is where the two AIs converge, and it is the shift CCM and CXM leaders should be planning for now.

The Bottom Line Generative AI gave our industry a faster pen. Agentic AI is offering something bigger, a system that can notice what is happening to a customer and respond to it. The organizations that win the next few years will not be the ones with the flashiest demo. They will be the ones who understood the difference early enough to govern it properly, managed their agents like the team members they effectively are and never lost sight of the customer while doing it.

MIA PAPANICALOU helps companies go paperless for transactional customer communications and works to improve those touchpoints through customized strategy and advisory services. She is a regular speaker and blogger on digital customer communication, digital maturity and improving the customer experience. ELIZABETH STEPHEN is an expert in CCM and helping clients utilize digital communications to meet their CX goals. As a true specialist in transactional communications, Liz has the ability to help companies make the needed microchanges that will immediately impact the customer experience, while putting the steps in place to make long-term changes. DOCUMENTmedia.com fall.2026

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THE AI-CX

CONNECTION

Why utilities must solve their data, integration and governance challenges before AI can deliver a better customer experience

By John Harney

mplementing AI is a complex process for electric utilities — but the work required to get there can also lay the foundation for stronger customer experiences. Two forces are reshaping how electric utilities operate. Utilities are transitioning from fossil fuels toward greener energy sources, a long-term process that requires improvements to the grid and the deployment of distributed energy resources (DER). At the same time, they are implementing AI to improve operations, management and decision-making. Neither transformation is simple. But the data, technology and organizational challenges utilities must address to successfully implement AI are closely connected to another priority: delivering better customer experiences. Culture Can Slow AI Adoption Utilities are risk-averse by design;

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reliability has historically been their mandate. Their technology environments also reflect decades of organizational separation, with planning, operations, customer service and IT often operating in silos. The data needed to support enterprise AI is consequently fragmented across systems and departments. Sharing and standardizing that information requires not only technology changes, but a new organizational mindset — one of the reasons many utilities find it difficult to move AI initiatives beyond the pilot stage. A Complex Value Chain Creates Complex Data Problems The utility value chain encompasses the entire journey of energy from source to consumption. Upstream activities involve energy sources such as solar, wind, water, oil, gas and coal. Midstream activities convert, process and transport those resources, while downstream

activities involve distribution, retail and ultimately customer consumption. Each stage presents different challenges for AI. Upstream, AI models may require granular weather, irradiance and equipment-level telemetry that utilities cannot always provide. Computer vision applications require large quantities of labeled data, while maintenance information may reside in paper records or legacy asset-management systems with inconsistent tagging. Within transmission and distribution (T&D), aging and heterogeneous equipment creates another challenge. Some assets lack the sensors and Internet of Things (IoT) instrumentation necessary for AI to detect faults or predict failures. Introducing greater automation also expands the cybersecurity attack surface. Downstream, rapid growth in electric vehicles, solar and data centers is creating new demand patterns. Utilities must increasingly coordinate large numbers of devices with different owners, standards and communication protocols. The common denominator is data. AI depends on consistent, high-quality, standardized information, while utilities frequently have the opposite: fragmented systems, inconsistent metadata and incomplete information. Breaking Down Data Silos Many systems supporting transmission and distribution were built for different purposes and operate separately. SCADA systems provide real-time telemetry, for example, while GIS platforms track asset locations. AI models, however, need unified datasets. Information from these systems must therefore be consistently labeled, governed and integrated to provide a more complete enterprise view. That creates challenges familiar far beyond the utility industry. Organizations pursuing AI frequently discover that their biggest obstacle isn’t the AI itself — it’s the fragmented information environment underneath it. Cybersecurity adds another layer. Integrating older, security-hardened systems with new data pipelines

VERTICAL FOCUS: UTILITIES requires appropriate access permissions, controls and authentication. Utilities must balance the desire for greater connectivity with the need to limit potential attack surfaces. The Challenge of Distributed Energy Distributed Energy Resource Management Systems (DERMS) illustrate just how difficult this integration can become. Utilities increasingly must manage large numbers of grid-connected resources they don’t own, including rooftop solar, home batteries, EV chargers, microgrids and other devices. The data generated by those resources can be fragmented, inconsistent or incomplete. AI performs best with consistent, high-quality information. Yet distributed resources can provide data in different formats and at different intervals — or provide limited realtime visibility at all. AI models used for forecasting, optimization or control must therefore make decisions based on partial information. DERMS must also integrate with numerous legacy and modern utility platforms, creating interoperability and latency challenges. The broader lesson is important: successful AI implementation depends heavily on an organization’s ability to connect information across systems, standardize it and make it available when and where it is needed. Governance Must Keep Pace with AI Regulation presents another challenge. Utilities operate in environments requiring auditability, documented assumptions, proven reliability and predictable behavior. AI systems that adapt or learn over time can conflict with regulatory expectations for stable and explainable operations. That makes governance an essential component of AI deployment rather than something that can be addressed after implementation. And the same principle applies to customer-facing AI. Organizations need to understand what their systems are doing, what data they are using and where human oversight remains necessary.

What AI Implementation Teaches Us About CX For all these challenges, utilities that successfully modernize their information environments can also create a stronger foundation for customer experience. AI can automate routine inquiries, improve responsiveness and use smart-meter data to provide customers with more personalized energy information. It can also help utilities move from reactive customer service toward more proactive customer care.

AI-powered CX is ultimately dependent on the information, integration and governance infrastructure behind it. But technology alone doesn’t guarantee a better experience. Even as utilities digitize customer interactions, many continue to struggle to scale personalization. Fragmented legacy systems such as CRM platforms can make it difficult to deliver seamless AI-driven experiences across channels. There are also risks inherent in over-automation. Customers can become trapped in poorly designed chatbot experiences, while complex inquiries can be mishandled without appropriate human oversight. Automation intended to make service more efficient can instead leave customers feeling that human support has disappeared. The lesson is one that extends well beyond utilities: AI-powered CX is ultimately dependent on the information, integration and governance infrastructure behind it. Utilities undertaking AI transformation should keep several principles in mind:

 AI is only as effective as the information supporting it. Fragmented, inconsistent or poorly governed data limits what even sophisticated models can accomplish.  Data silos eventually become customer experience problems. When systems can’t communicate, organizations struggle to create consistent and personalized interactions across channels.  Legacy modernization and AI strategy are interconnected. AI cannot simply be layered on top of decades of disconnected technology without addressing integration.  Governance must be designed into AI from the beginning. Auditability, security, reliability and human oversight become increasingly important as AI moves into operational and customer-facing environments.  Automation isn’t synonymous with customer experience. Efficiency matters, but organizations must preserve effective paths to human assistance when customers need it. Building the Foundation First Implementing AI across an electric utility is an arduous undertaking. Large utilities serve hundreds of thousands — or even millions — of customers while operating complex, highly regulated and safety-critical infrastructure. Outside expertise may be valuable in helping utilities establish AI methodologies, address specialized technology challenges and build internal capabilities. But the larger lesson is that AI transformation isn’t simply an AI project. It is also a data, integration, governance and organizational transformation. Utilities that address those foundational issues aren’t just better positioned to deploy AI. They’re also better equipped to use it to create the connected, responsive and personalized customer experiences their customers increasingly expect.

JOHN HARNEY is a veteran Intelligent Information Technology journalist and consultant. He can be reached harneyj65@gmail.com and 240.674.1309. DOCUMENTmedia.com fall.2026

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s healthcare communications expand across digital and print channels, organizations must protect sensitive information while improving the health plan member experience. Healthcare communications contain sensitive information related to a person’s health history, finances and personal details. Critical documents such as billing statements, explanations of benefits, appointment information and care instructions all need to reach the right recipient in a way that is secure, accessible and easy to understand. How organizations manage that delivery can affect health plan member experience, and the trust that’s been built over time. As communication options expand across print and digital channels, healthcare organizations need a strategy that protects sensitive information while giving recipients practical ways to access it.

Convenience Without Security Falls Short

BUILDING TRUST INTO EVERY HEALTHCARE COMMUNICATION How security, accessibility and omnichannel delivery shape the health plan member experience By Jason Pothen 24

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The Health Insurance Portability and Accountability Act (HIPAA) lays down protections for individuals’ health information. For electronic health information, HIPAA requires regulated organizations to implement administrative, physical and technical safeguards to protect its confidentiality, integrity and availability. Patients and health plan members also expect convenient ways to receive information. While digital communications have become more common, print remains a preferred channel depending on the circumstances. Some recipients may be more comfortable receiving important healthcare information by email, while certain pieces may be communicated in print to support a multichannel messaging strategy. Depending on the type of communication and the recipient’s preferences, information should be made available through a secure portal or other protected digital channels. It’s why healthcare organizations must support a variety of communication channels from print to digital. An

VERTICAL FOCUS: HEALTHCARE omnichannel approach gives health plan members more choice while helping organizations maintain security and consistency across communications.

Print and Digital Working Together Managing print and digital communications together gives healthcare organizations flexibility to meet different needs. Centralized workflows and consistent document standards can also make communications easier to manage. Regardless of the channel, communications need to remain private, accurate and accessible.

AI Enables New Opportunities and Considerations Artificial intelligence (AI) is becoming deeply embedded in healthcare communication workflows. It can be used to analyze communication patterns, simplify language, enhance content personalization and identify inefficient processes. While AI-powered features represent a significant breakthrough for the healthcare industry, clear controls around its use must be established. Organizations need to understand what data an AI system uses, where that information is processed, who can access it and how its outputs are reviewed. Whenever possible, AI-powered communication workflows should minimize exposure to personally identifiable information (PII) and protected health information (PHI). When sensitive data is required, organizations need appropriate privacy, security, access and governance controls throughout the process. AI should be used within existing privacy, security and governance practices. And human oversight is especially critical for communications containing sensitive health, financial or coverage information.

Build Security into Every Communication Workflow Secure document delivery also depends on how documents are created, accessed, delivered and stored. Healthcare organizations need to create a framework to protect sensitive information throughout the health

plan member journey. The framework should cover authentication, access management, auditing and secure transmission. Building security directly into communication workflows makes it part of the process rather than an extra step for employees or recipients.

Connecting the Communication Ecosystem Healthcare organizations often manage many types of communications across print and digital channels. When those processes are handled separately, it can make communications harder to manage and keep consistent.

Trust isn’t built through security alone. It’s built when communications are secure, accessible, understandable and delivered in the way members expect. A customer communications management (CCM) platform can help bring these processes together, giving healthcare organizations a centralized way to manage how communications are created, delivered and tracked while applying appropriate controls throughout the process. This includes:  Secure creation and delivery of printed communications  Digital delivery through email, SMS, and health plan member portals  Support for health plan member communication preferences Managing these functions together makes it easier for healthcare organizations to oversee communications from start to finish. It can also reduce the need to manage separate systems and processes for print and digital delivery.

A centralized approach can also help create a consistent experience for health plan members. Whether information arrives by mail or through a digital channel, it should be clear, accurate and easy to recognize. A CCM platform can help healthcare organizations manage that experience while keeping security essential to the communication process.

Accessibility Is Integral to the Experience Health plan members also need to be able to access and understand the information they receive. Plain language best practices, mobile friendly digital experiences, accessible document design and channel choice all play a role. Digital-first communications can create barriers if some health plan members have difficulty accessing them. Healthcare organizations need to consider security, accessibility and health plan member experiences when planning their communications. Even the most secure document has limited value if the recipient can’t easily access or understand it.

Creating a Connected Communication Strategy Healthcare communications will continue to change as organizations expand digital services, adopt AI and respond to new cybersecurity risks. Healthcare organizations don’t necessarily need more channels or technology. They need a coordinated way to manage print and digital communications while maintaining security and accessibility. Giving health plan members appropriate ways to receive and understand important information can improve their experience and build trust in how their sensitive information is handled.

JASON POTHEN, Senior Vice President of Sales, has 22+ years of experience across print and digital communications, serving clients in a range of industries. As Senior Vice President, Sales, Jason focuses on building long-term client relationships, driving account growth, and resolving challenges. DOCUMENTmedia.com fall.2026

CONTENT COMPLIANCE BY DESIGN EMBEDDING ACCESSIBILITY AND PRIVACY FROM DAY ONE BY ERIC RIZ

or years, organizations have treated accessibility and privacy as checkpoints near the end of the content lifecycle. A document gets written, a website built or an application launched, and only then does someone ask whether it meets accessibility, privacy, security or regulatory requirements. Compliance is applied to finished work rather than shaping how it is created. That approach becomes increasingly difficult to sustain as the volume and velocity of enterprise content grow. Organizations now produce enormous amounts of information across Microsoft 365, websites, collaboration platforms, customer portals, business applications, AI assistants and automated workflows. Increasingly, that content is summarized, classified, transformed and generated by artificial intelligence. The

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scale of the environment has changed, and our approach to compliance must change with it. Content Compliance by Design starts with a different premise: accessibility and privacy should not be corrections applied to finished content. They should be intentionally embedded into the content lifecycle from the moment information is created. Instead of asking how to make content compliant after the fact, organizations should create environments where compliant content is the natural outcome of everyday work.

Compliance Debt Is Digital Debt Most technology leaders understand technical debt. Organizations make small compromises to move quickly, and those compromises accumulate until maintaining the environment becomes

expensive and difficult. Enterprise content creates a similar problem. Every inaccessible PDF, improperly classified document, overshared Teams workspace, unnecessary personal information, abandoned SharePoint site and uncontrolled AI-generated document adds liability. Individually, these problems may appear manageable. Across hundreds of thousands or millions of documents, messages, sites and records, they become compliance debt. Eventually, organizations struggle to answer basic questions:  Who should have access to this information, and who actually has access?  Does this document contain personal, confidential or regulated information?  Can someone using assistive technology properly navigate and understand it?  How long should it be retained, and when should it be deleted?

SUBSCRIBE FOR FREE! or PDF and later discovers missing alternative text, inconsistent headings, inaccessible tables, insufficient color contrast, ambiguous links or poor document structure. The organization then spends additional time and money correcting problems that could often have been prevented.

The cheapest compliance problem to solve is the one the organization never creates.

 Should it be available to search, Copilot, ChatGPT or another AI system?  Can it safely be shared externally? When those questions cannot be answered consistently, the problem is no longer simply compliance. It is an information architecture problem. Organizations have accumulated information faster than the governance needed to manage it. The better question is not, “How do we make all of our existing content compliant?” It is, “How do we design an environment where compliant content is the easiest content to create?”

Accessibility Cannot Be a Final Formatting Exercise Accessibility is still frequently approached as remediation. Someone creates a report, presentation, website

Accessibility becomes easier when it is moved upstream. Accessible templates, built-in heading hierarchies, publishing workflows that prompt for alternative text, automated accessibility checks, reusable design components and procurement standards can make accessibility part of creation rather than cleanup. The objective should not be to turn every employee into an accessibility specialist. It should be to make accessible behaviour the default. Good governance reduces the number of compliance decisions employees need to make themselves.

Privacy Should Start Before the Data Exists Privacy often suffers from the same backwards thinking. Organizations devote enormous effort to protecting information after it has been collected while spending comparatively little time asking whether it needed to be collected at all. One of the most effective privacy controls is simple: do not collect information you do not need. Before another field is added to a form, CRM system, SharePoint list, application, registration process or AI workflow, organizations should ask why the information is being collected,

what legitimate business purpose it serves, who needs access, how long it should be retained, whether the process could operate without it, and what should happen when the original purpose disappears. These questions move privacy into the design process. Rather than accumulating enormous repositories of personal information and subsequently trying to secure them, organizations reduce the amount of sensitive information entering the environment. Data minimization therefore becomes more than a privacy principle. It becomes an architectural strategy. Every unnecessary piece of information creates another object that may need to be secured, classified, retained, discovered, disclosed, deleted and protected from inappropriate AI exposure. Reducing unnecessary data reduces unnecessary risk.

AI Makes Content Compliance More Urgent Generative AI increases the importance of getting this right because traditional enterprise search and AI operate differently. Search generally waits for someone to know what they are looking for. AI can interpret information, combine repositories, identify relationships, summarize large volumes and surface information employees may never have discovered. That creates enormous productivity opportunities, but it also exposes weaknesses in information governance. AI does not necessarily create an organization’s information problems; in many cases, it reveals problems that were already there. If permissions are overly broad, AI can make broadly accessible information easier to discover. If documents are poorly classified, AI systems may have limited signals about sensitivity or intended use. If content is poorly structured, AI-generated summaries may suffer. If unnecessary personal information has accumulated, AI increases the ability to find, correlate and interpret it. This creates a direct relationship between AI readiness and content readiness. Organizations cannot responsibly DOCUMENTmedia.com fall.2026

build an intelligent layer over an information environment they do not understand. Before asking what AI should be allowed to do, leaders need to understand what information AI can see.

Compliance Must Follow the Entire Content Lifecycle Content Compliance by Design requires organizations to stop thinking about governance as a single checkpoint and instead consider the entire information lifecycle: creation, classification, storage, access, sharing, discovery, use, retention and disposal. At each stage, governance controls can be intentionally embedded. Templates and authoring tools can promote accessible content and limit unnecessary sensitive-data collection; classification, sensitivity and retention policies can be applied based on context; approved repositories can replace unmanaged storage; and identity, permissions and role-based access can restrict information to those who need it. Sharing policies can prevent inappropriate external distribution, while search and AI systems can honor the same permissions, classifications and information boundaries. Retention and disposal controls can ensure information is kept only as long as required and defensibly deleted when it no longer serves a legitimate purpose. Governance does not exist at one point in this lifecycle. In a modern enterprise, it exists everywhere information moves.

Automation Changes the Economics of Compliance Historically, stronger compliance often meant more manual effort: more forms, reviews, approvals, audits and people checking the work of other people. That model becomes increasingly unrealistic as organizations create more content and introduce AI into everyday business processes. Modern technology can change the economics of compliance by embedding controls directly into workflows. Sensitive information can be automatically identified or classified. Publishing workflows can flag accessibility problems. Forms can limit unnecessary data collection. 28

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Retention policies can manage information according to business rules. AI assistants can operate within identity and permission boundaries, and data loss prevention controls can intervene when sensitive information is about to be shared inappropriately. This represents a shift from policing behavior to engineering behavior. Human accountability remains, but judgment can focus where it adds the most value while technology handles repeatable controls.

Good governance reduces the number of compliance decisions employees need to make themselves. Good Governance Should Become Almost Invisible Consider two organizations. The first publishes lengthy policies covering accessibility, privacy, classification, retention, sharing, security and acceptable AI use. Employees complete annual training and are expected to remember those rules across hundreds of daily decisions. The second still has policies and training, but its digital environment reinforces them. Accessible templates are available by default. Classification is suggested automatically. Sharing controls respond to sensitivity. Retention occurs behind the scenes. AI systems inherit permissions. Forms collect only necessary information. Employees receive contextual warnings when an action creates risk. The second environment is more likely to achieve sustainable compliance because it does not depend on employees remembering hundreds of rules. Policy,

training and accountability still matter, but the environment itself becomes an active participant in governance.

From Compliance Obligation to Organizational Capability The future of compliance will not be defined by organizations that write the most policies. It will increasingly be defined by organizations that build digital environments where responsible behavior happens naturally. That requires accessibility, privacy, information governance, security, technology, communications and business teams to recognize that they participate in the same information lifecycle. Accessibility cannot begin when someone asks whether a finished document is accessible. Privacy cannot begin when sensitive information is discovered in the wrong place. Governance cannot begin when information becomes a problem, and AI governance cannot begin after AI has already been given access to everything. Content Compliance by Design is straightforward: design the controls when you design the content and the systems that create it. Make accessibility part of the template, privacy part of data collection, classification part of creation, permissions part of architecture, retention part of the lifecycle and AI governance part of information governance. The cheapest compliance problem to solve is the one the organization never creates. As humans and AI systems generate, transform and distribute more information than ever before, embedding accessibility and privacy from day one will become more than a regulatory strategy. It will become a fundamental requirement for building a digital enterprise that employees, customers, regulators and increasingly machines themselves can trust.

An established leader focused on corporate efficiency, strategy and change, ERIC RIZ founded data analytics firm VERIFIED and Microsoft consulting firm eMark Consulting Ltd. Email eric@ericriz.com or visit www.ericriz.com for more information on how to govern your data journey.

WHAT THE ANALYSTS SAY…

Intelligent Document Processing (IDP) and Insurancespecific IDP Products PEAK Matrix Assessment 2026 Intelligent Document Processing (IDP) continues to evolve as enterprises expand automation and incorporate generative and agentic AI into documentintensive workflows. This report examines the global IDP market, including insurance-specific solutions, and how providers are improving document understanding, data extraction, workflow orchestration and integration. It also explores key adoption challenges, including data variability, governance and human validation, while evaluating provider capabilities and considerations to help organizations select solutions that support efficiency, compliance and long-term automation goals.

Aspire CCS Explores the Strategic Case for CCM-CXM Convergence Aspire CCS’ latest Market Trend Report makes the case for bringing Customer Communications Management (CCM) and Customer Experience Management (CXM) together into one unified system of customer engagement. While seven in ten organizations have begun aligning the two functions, only 13% have achieved full integration — and those that have are already pulling ahead. The report examines the structural, technological, and governance drivers reshaping this convergence, and offers guidance for organizations at every stage of maturity. Next in the series: an exploration of Rich Communications Services (RCS) and the next generation of customer communications. To learn more about Aspire CCS’ library of market trend reports, visit our website or contact Will Morgan at will.morgan@aspireccs.com.

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The Aragon Research Globe for Workflow and Content Automation, 2026 The workflow and content automation market is poised for more change in the next year than in the last ten. Content Assistants and AI Agents will help knowledge workers get work done faster. We evaluate 13 key providers that are leading the charge in the WCA market.

QKS Group’s Customer Communications Management (CCM) market research examines the global market, including emerging technologies, key trends and future outlook, to help technology vendors shape growth strategies and buyers evaluate provider capabilities, differentiation and market position. The research features QKS Group’s proprietary SPARK Matrix, which evaluates and positions leading global CCM vendors, including Adobe, OpenText, Quadient, Smart Communications, Messagepoint, Doxim and others. According to Principal Analyst Saurabh Raj, the CCM market has reached an inflection point as traditional strengths such as template flexibility and output volume give way to content intelligence, lowcode authoring and AI-native workflows, with vendors increasingly differentiated by how quickly customers can put these capabilities to use.

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