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CLOUDED WITH POSSIBILITIES: HOW TODAY’S CIOS ARE BUILDING THE FUTURE
Afew years ago, during a layover at a small airport, I overheard a frustrated business traveler mutter, “I’ve got everything in the cloud, and yet I still can’t get a decent Wi-Fi signal.” It made me laugh—but it also stuck with me. Because while the cloud has become an integral part of how we live and work, truly harnessing its potential is still a journey for many organizations.
Let’s be honest—cloud used to be a buzzword. Now, it’s the backbone. Businesses aren’t just migrating to the cloud to save money or streamline operations anymore. They’re building entirely new strategies, services, and even business models around it. Generative AI, edge computing, serverless architecture—these are no longer just tech trends; they’re active tools in the CIO’s arsenal.
But here’s the thing: with great innovation comes great complexity. Have you ever felt like the pace of change is outpacing your team’s ability to keep up? You’re not alone. Hybrid workforces, evolving security threats, talent gaps—it’s a lot to manage. And yet, every challenge also opens a door to rethink, reimagine, and rebuild with clarity and purpose.
This issue of CIO Magazine dives headfirst into that conversation. Our cover story features Lara Rubbelke, CTO of Microsoft Americas, who offers an unfiltered look into how enterprises can make the most of their cloud investments. From solving big business problems to scaling innovation, Lara shares what it takes to turn vision into action—without losing sight of what matters.
You’ll also find stories about how AI is reshaping cloud use, how multi-cloud strategies are evolving, and how cybersecurity remains mission-critical in this hyper-connected age. So, here’s our ask: read, reflect, and maybe even rethink your own cloud journey. What’s working? What’s holding you back? And how can you lead your organization to not just adapt, but truly thrive?
Let’s keep this conversation going—because the future isn’t just coming. It’s already here, floating on a server somewhere, waiting for bold leaders like you to shape it.
Happy reading—and don’t forget to check your Wi-Fi.
Sarath Shyam
LARA RUBBELKE
CHIEF TECHNOLOGY OFFICER, MICROSOFT
AMERICAS
EMPOWERING THE NEXT WAVE OF TECH PIONEERS
COVER STORY
Howard Miller
14 Chief Information Officer, UCLA Anderson School of Management
The Skills Modern IT Leaders Need in a Tech-Evolving Landscape
42
Alasdair Redmond
42 Chief Information Officer, Endava
AI and Digital Friction: Overcoming Resistance to New Technologies in the Workplace
Ali Katkhada
26 Group CIO, Depa Group Transformative Leadership in the Fourth Industrial Revolution
Alexander Graf
36 CIO, HUBER+SUHNER
The Acceleration of the Digitalization Journey – AI as a Booster
Don Cox
48 Chief Information Security Officer, American Public Education, Inc.
Building a Strong AI Governance, Risk, and Compliance (GRC) Program: A CIO-CISO Collaboration Guide
LARA RUBBELKE
CHIEF TECHNOLOGY OFFICER, MICROSOFT AMERICAS
EMPOWERING THE NEXT WAVE OF TECH PIONEERS
As the Chief Technology Officer for Microsoft Americas, Lara Rubbelke works with customers to help them with their most strategic technology initiatives that drive their innovation and digital transformation. With a passion for leveraging cutting-edge solutions and solving complex business challenges, Lara is dedicated to fostering a culture of innovation and collaboration across our industries.
For over 25 years Lara has worked with organizations to create business value, optimize operations and achieve sustainable growth by harnessing the power of technologies across Cloud Computing, Artificial Intelligence, Data Analytics and Systems, and Cybersecurity. She is committed to building the next generation of technology leaders and is a prominent voice in the technology community through industry events and forums.
Recently, in an exclusive interview with CIO Magazine, Lara shared insights on the future of cloud-enabled innovation and its implications for business and society, highlighted the key qualities that define a successful CTO, personal hobbies and interests, future plans, words of wisdom, and much more. The following excerpts are taken from the interview.
Hi Lara. What excites you most about the future of cloud computing and its potential impact on businesses and society?
What excites me most is the pace of innovation and the opportunity it creates to reimagine how we work, connect, solve problems and realize new opportunities. Cloud computing, especially when paired with AI, is empowering organizations to enrich the employee experience, reinvent customer engagement, reshape business processes, and bend the curve on innovation. It’s not just about technology for technology’s sake—it’s about enabling people to focus on what really matters: creativity, insight, and impact. We are unlocking potential—both for businesses to grow and for society to benefit in areas like education, sustainability, and healthcare. That kind of transformation is both exciting and deeply meaningful.
What do you love the most about your current role?
I’m lucky that my job is also my hobby—I get to work with incredibly passionate people to build impactful cloud solutions. As CTO for Microsoft Americas, I collaborate directly with people from all types of organizations who are creating new applications and experiences on our platform. I love the hands-on work of co-creating, discovering patterns, and sharing best practices to help our customers innovate.
What do you believe are the most important qualities or characteristics for a CTO to possess, and how do you embody those qualities in your own role?
Curiosity, collaboration, and a growth mindset are essential. The technology landscape changes
quickly and staying relevant means continuously learning—I carve out time every week to explore new trends, tools, and ideas. Just as important is the ability to listen. As CTO, I spend a lot of time with customers and teams, and I’ve found that the best solutions often start with bringing people together to understanding someone else’s perspective. Listening fuels innovation, builds trust, and keeps us focused on what truly matters.
What role do you think collaboration and partnerships play in driving technological advancements?
Collaboration is critical. The most meaningful progress happens when different perspectives come together to solve real challenges. In previous roles, I led engineering teams where Microsoft engineers worked side by side with customer engineers, sometimes for six months at a time, to co-innovate. That kind of deep partnership builds trust, accelerates learning, and leads to solutions that are both technically strong and grounded in real-world needs. The best ideas don’t happen in isolation — they’re built together.
As CTO for Microsoft Americas, I collaborate directly with people from all types of organizations who are creating new applications and experiences on our platform
Collaboration is more important now than ever before. The rate of change in the models, tools, platforms, and frameworks to build new AI applications is faster than ever. Collaboration enables all of us to learn with and from each other. We capitalize on the collective IQ to move at a rapid pace while learning new ways to engineer in an AI world.
How do you stay current with the latest developments in technology, and what sources do you rely on for information?
For me, it starts with prioritizing learning and making learning a regular habit. Work is infinite, and it is critical that we prioritize time to focus on learning. I block time each week to focus on learning, and find ways to connect with others who are building solutions to understand new approaches. Some of my best insights come from conversations with customers and colleagues who are pushing the boundaries in their own work. I also
stay current by listening to books (I am an audio book junkie!), following tech news, listening to podcasts, and staying connected with industry peers. It’s less about one single source and more about staying curious and open to learning from everywhere.
What are some of your passions outside of work? What do you like to do in your time off?
I love to read—I typically read 2-3 books a week. It’s how I unwind and keep learning at the same time. I also really enjoy traveling and discovering new food, architecture, and meeting people all over the world. I travel with my sons when they can fit it around their university classes, they are the best travel buddies. Finally, I try to regularly get out for a run. Those things keep me grounded and energized.
What is your secret to striking a worklife balance?
There is no secret, it is difficult.
I focus on making time for what I love— reading, running, and spending time with family and friends. That mix helps keep everything in perspective.
It is also important to recognize that worklife balance changes over time and I regularly evaluate my personal and professional priorities. When my children were young, my partner and I made career choices that aligned with our family priorities. As our family grew older, I was able to make different career choices that reflected our evolving needs. It isn’t always easy, and in the moment, you can feel unsure about these
decisions. However, I never look back and consider any of my choices as “sacrifices”.
Which technology are you investing in now to prepare for the future?
I’m currently focusing on multi-agent development and agentic solutions We are still so early in what we know about AI and AI solution architecture. We are working closely with many customers who are incorporating these innovations to drive new business opportunities.
Longer term, I'm excited about quantum computing. Microsoft's recent introduction of the Majorana 1 chip, powered by a new topological core architecture, marks a significant step toward scalable and fault-tolerant quantum systems. This innovation brings us closer to practical quantum computing solutions that could transform industries by solving complex problems more efficiently.
What is your biggest goal? Where do you see yourself in 5 years from now?
I’m focused on equipping our industry with the next generation of technical talent. There’s so much change happening in our industry – this current AI wave has introduced the most rapid change to how we build solutions, what solutions we build, the tools needed to support these solutions, and so much more. It’s important to make sure others are ready to lead through it, that we understand the context of our history while focusing on the right changes. When I’m helping people grow, ask the right questions, solve the right problems, and make real impact, then I’m in the right place.
We capitalize on the collective IQ to move at a rapid pace while learning new ways to engineer in an AI world
What advice would you give to aspiring technologists looking to grow their careers in the cloud computing space?
My advice is to keep building and updating your skills. Make space in your schedule to learn. Technology moves fast, and having a strong, adaptable skill set gives you the flexibility to take on new challenges and opportunities as they come.
Howard Miller
Chief Information Officer, UCLA Anderson School of Management
The Skills Modern IT Leaders Need in a Tech-Evolving Landscape
Howard Miller is currently the Chief Information Officer at UCLA Anderson School of Management. Prior to joining UCLA, Howard was the Acting Chief Information Officer and CISO at the Columbia University School of Business, leading both the Information Security and Project Management Office functions. Howard is an accomplished executive and senior IT leader with expertise in the design, development, and deployment of technical strategy and policy. Howard holds an MBA degree in Management Information Systems and a Bachelor’s Degree in Computer Science from Rensselaer Polytechnic Institute. Howard also has several professional certifications, including PMP, CISM and CRISC.
In a recent interview with CIO Magazine, Howard Miller discussed his experience with leadership and technology. He shared his views on IT strategy evolution, technology investments, innovation, and agility, and many more.
What are some of the key leadership lessons you've learned throughout your career in IT strategy?
There are several key takeaways for me regarding good leadership. You need to be a good listener; you need to lead with empathy, and you need to build great relationships both within your team and with your business stakeholders. I’ve been able to sell my vision, both to my team and as it aligns to delivery on the school’s strategic plan.
How has IT strategy evolved over the past decade, and what major shifts do you foresee in the next five years?
Our IT strategy has changed about 2 or 3 times at my current employer in 6 years. After performing an initial assessment in the first 90 days, I was able to set a direction that embraced current technology, modernized a technology stack, and brought innovation to the forefront. In the middle, we had a good reminder that our
business relationship mattered, and we needed to deliver on an improved customer experience. More recently, we’ve been focused on data, cybersecurity and AI. AI is here for a while, and quantum computing could be on our horizon in the next several years. Nevertheless, I foresee a continued focused on these three items, data, cyber and AI for a while. I don’t prefer to focus several years out, as a reminder, we’ve only really known about generative AI for a little over two years.
What are the biggest challenges organizations face when aligning IT strategy with overall business objectives?
The biggest challenges most organizations face with aligning IT strategy to overall business objectives are usually one of several things. Either IT doesn’t understand or doesn’t care to align to the business strategy. Additionally, some organizations suffer from having proper governance structures, in which case resources might be improperly allocated to those items most important to the business.
With AI, cloud computing, and cybersecurity becoming more critical, how should CIOs and IT leaders prioritize their technology investments?
Great question – and in general, those are the primary places where my technology investments are being made these days. The only item potentially missing from that list is data. Especially as data is the engine that feeds the AI. Regardless, the answer most closely matches the previous question – ensuring whatever investments are made in technology most closely align to the business objectives and business strategy, and in priority order to the extent possible.
How can businesses balance innovation with risk management in their IT strategies?
Those businesses that are most successful figure out a way to innovate, period. There are lots of cliches like “fail fast”, etc. but playing it too safe can ultimately be too limiting to your business. I think you need, as a leader, to figure out when it makes sense to take chances, find products or ideas that can transform your
IN 2025, IT LEADERSHIP PLAYS A SIGNIFICANT ROLE IN DRIVING DIGITAL TRANSFORMATION. TODAY’S ORGANIZATIONS EXPECT THEIR IT LEADERS TO BE AT THE FOREFRONT OF DIGITAL TRANSFORMATION
THE BEST WAY TO FOSTER A CULTURE OF INNOVATION AND AGILITY WITHIN IT TEAMS IN TO LEAD BY EXAMPLE, TRY NEW THINGS, CHALLENGE PEOPLE TO STEP OUT OF THEIR COMFORT ZONES, AND IDENTIFY SOLUTIONS THAT WILL ADD VALUE TO YOUR BUSINESS
business or provide competitive advantage, and then confidently execute with conviction.
What role does IT leadership play in driving digital transformation, and how can leaders ensure companywide adoption?
In 2025, IT leadership plays a significant role in driving digital transformation. Today’s organizations expect their IT leaders to be at the forefront of digital transformation. IT leaders have never had a better opportunity to deliver business objectives with technology and
generally try to ensure company-wide adoption via organization change management techniques – communication and clearly articulating the benefits of the change.
What skills do modern IT leaders need to stay ahead in an increasingly techdriven business environment?
There are several skills that modern IT leaders need to stay ahead, the most important of which is to truly understand the value of business relationships. Additionally, as previously discussed, being well-versed in as many things AI, data, and cybersecurity-related, even at a high-level, are extremely important today.
How do you foster a culture of innovation and agility within IT teams to support long-term strategic goals?
The best way to foster a culture of innovation and agility within IT teams in to lead by example, try new things, challenge people to step out of their comfort zones, and identify solutions that will add value to your business. I continue to identify and work with business partners who have solutions that align to my goals of reducing technical debt, adding in automation, making us more secure, and making sure that we are working on things that are technically modern and relevant.
What advice would you give to aspiring IT leaders looking to make a lasting impact in their organizations?
Take risks, try to get noticed, volunteer, and speak with your leadership about your individual career and developmental plan. If you wait around for someone to give it you, you’ll likely be waiting a long time, so be proactive.
Harnessing Innovation for a Better Future Katherine Boiciuc
CTO Oceania, EY
Katherine Boiciuc is the Oceania Chief Technology and Innovation Officer at Ernst & Young Services Pty Limited. With over two decades of experience, Katherine is recognized as one of Australia's leading professionals in technology and innovation. She has a proven track record of leading global teams at Telstra and currently serves on the boards of the NSW Bureau of Health Information and Infoxchange.
Katherine holds an MBA and a Master of Leadership from Deakin University. She is also a graduate of the London Business School, where she studied Managing the Company of the Future, and is an accredited Futurist with the Institute for the Future in California. Her expertise spans across various domains, including AI, technology strategy, and innovation, making her a sought-after speaker and thought leader in the industry.
Recently, in an exclusive interview with CIO Magazine, Katherine shared insights on the role of artificial intelligence in shaping the future of business, personal hobbies and interests, future plans, words of wisdom, and much more. The following excerpts are taken from the interview.
Hi Katherine. What drives your passion for technology and innovation?
Growing up, our family motto was there is no such place as far away. Dad was in the army and mum in Singapore working at a tech magazine. I became an early adopter of tech so I could remain connected to the people I loved. The power that technology has to connect and unite effort to unlocking the extraordinary is why I love working at the frontier of technology.
Technology and innovation are powerful levers for positive change. I’m driven by the opportunity to solve complex problems, ignite ambitious agendas, and help organisations and people thrive in a rapidly evolving world. The pace of technological advancement— especially in AI and emerging tech—means we’re constantly reimagining what's possible. Having a chance to shape the future is where I get my energy.
What do you love the most about your current role?
What excites me most is leading EY’s Oceania region through our scaling of AI across our services and helping clients harness technologies like generative AI and advanced computing to unlock value. Watching people master AI and creating the conditions for Super Work has been a career highlight.
Can you tell us more about Super Work?
The Super Learner, Super Work, and Super Organisation model is EY's approach to integrating AI into the workplace while keeping the human element at the centre.
Super Learner: This phase focuses on upskilling employees with AI literacy and advanced data handling skills through targeted training programs and micro-credentialing. By developing prompt mastery, employees can efficiently leverage AI tools to solve problems in real-time.
Super Work: In this phase, AI is strategically integrated into daily operations to augment human capabilities. This involves designing role-specific agentic AI tools, automating routine tasks, and fostering collaborative intelligence where teams work alongside AI to enhance productivity and innovation.
Super Organisation: The final phase involves rethinking business models to fully capitalise on AI's potential. This includes redefining workflows, creating new value propositions, and ensuring that AI-driven decision-making aligns with the organisation's strategic goals. By following this model, organisations can create a dynamic and scalable approach to work that transcends traditional functional siloes and drives sustained performance.
What role do you think artificial intelligence will play in shaping the future of business?
AI will be a defining force in business, driving efficiency, growth, and new business models. It’s essential, however, that we adopt AI with higher purpose in mind. To build a better working world ensuring safe and responsible adoption. Balancing productivity gains with ethical considerations, transparency, and human-centric values. Businesses that embrace AI with strong governance and a focus on upskilling will lead the way in innovation.
BUSINESSES THAT EMBRACE AI WITH STRONG GOVERNANCE AND A FOCUS ON UPSKILLING WILL LEAD THE WAY IN INNOVATION
You are a member of Chief Executive Women (CEW) organisation. Can you please tell us about CEW and what made you become a part of it?
Chief Executive Women (CEW) is a community of senior women leaders committed to enabling women leaders and driving gender equality. I joined CEW to connect with and learn from inspiring women, share experiences, and collectively create pathways for more women to reach executive roles and shape the future of leadership.
What does the term "authentic leadership" mean to you?
Authentic leadership is about leading with your whole self. There is no room for ego. You provide clarity, vision and outcome orientated leadership. It means bringing your true self to work, building trust, and empowering others to do the same. Authentic leaders inspire teams by being transparent, listening deeply, and staying true to their values.
What are your thoughts on diversity and inclusion in tech?
Only 22% of the AI workforce and 14% of AI executives are women. We stand on the edge of an era that is scaling AI across all industries across work and home. I am very concerned at the lack of diversity in the workforce that is making choices on how AI shapes the future.
Diversity and inclusion are critical for innovation and solving the world’s toughest challenges. The tech industry has made progress, but there’s more to do.
DIVERSITY AND INCLUSION ARE CRITICAL FOR INNOVATION AND SOLVING THE WORLD’S TOUGHEST CHALLENGES
What are some of your passions outside of work? What do you like to do in your time off?
Outside of work, I’m passionate about giving back through board roles with organisations that make a positive impact. I also enjoy exploring new technologies attending music concerts, and spending quality time with my family.
What is your biggest goal? Where do you see yourself in 5 years from now?
My biggest goal is to enable 100k+ women to enter the AI workforce in Australia by 2030. I enjoy empowering leaders and organisations to be future ready, with a strong focus on ethical innovation and inclusive leadership. In five years, I see myself at the forefront of driving
responsible tech adoption globally, mentoring emerging leaders, and helping shape policy for a better digital future.
What advice would you give to women looking to pursue careers in technology?
- Network like your career depends on it—because it does. Build trusted connections within and outside your organisation.
- Back yourself and dream big; you are enough to achieve whatever you set your mind to.
- Seek mentors, stay curious, and don’t be afraid to show your personality—authenticity attracts opportunities.
- Remember, qualifications matter, please do formal AI training in 2025.
Wa n t t o S e l l o r fi n d
I nve s t o rs f o r yo u r
B u s i n e s s ?
TRANSFORMATIVE LEADERSHIP IN THE FOURTH INDUSTRIAL REVOLUTION
Ali Katkhada Group CIO, Depa Group
Ali Katkhada, Group CIO at Depa Group (a publicly listed corporation), is a distinguished executive with a focus on digital transformation and corporate innovation. Ali boasts a proven track record in international markets, excelling in board-level interactions and cross-functional team leadership. His areas of expertise include IT Governance, innovation strategy, a cohesive digital vision, enterprise architecture, and emerging technologies such as AI, Web 3.0, blockchain, and decentralized finance (DeFi). Ali is a highly certified professional, holding a Doctorate in Artificial Intelligence and a Master's in Engineering & Technology Management from the United States. He is a sought-after advisor and public speaker, and a multiple recipient of the World Top CIO Award.
Navigating AI, Quantum Computing, Blockchain, NFT, Smart Contracts, Metaverse, and digital twins in Corporate Strategy
The Fourth Industrial Revolution, characterized by the fusion of technologies that blur the lines between physical, digital, and biological spheres, is reshaping industries at an unprecedented pace. In this transformative era, leadership demands more than traditional strategies—it requires visionary thinking, technological fluency, and the ability to navigate emerging digital landscapes. At the core of this revolution are cutting-edge technologies such as blockchain, NFTs, smart contracts, the metaverse, artificial intelligence
(AI), and quantum computing, which are coming to corporate use sooner than expected. Each plays a pivotal role in corporate transformation.
The Essence of Transformative Leadership:
Transformative leadership is about more than just leading change; it is about inspiring and guiding organizations through continuous evolution. CIOs today must foster a culture that embraces innovation, resilience, and digital readiness. As business models evolve rapidly, transformative leaders are distinguished by their ability to anticipate change and empower their teams to adapt.
TRANSFORMATIVE LEADERS UNDERSTAND THAT AI SHOULD NOT BE TREATED AS A SERIES OF ISOLATED PROJECTS BUT AS AN INTERCONNECTED ECOSYSTEM THAT ENHANCES DECISION-MAKING AND OPERATIONAL EFFICIENCY
As technology becomes increasingly accessible, with cloud and AI prevalent in virtually every workplace, one of the critical attributes of transformative leadership is aligning technology with business objectives. Leaders must demonstrate the value of technology to the business by communicating in a language that resonates with business stakeholders. Furthermore, they must cultivate a mindset that encourages experimentation and data-driven decision-making. Prioritizing innovation and being open to disruptive technologies are essential, while creating an environment that nurtures creativity and minimizes resistance to change.
The Role of Artificial Intelligence: Strategic Integration
Artificial intelligence, although currently perceived as a buzzword, will soon become seamlessly integrated into our daily lives— just as happened with technologies like 5G, virtualization, and cloud computing. AI has already revolutionized many business functions, from predictive analytics to customer service automation. However, its true power lies in strategic integration across the enterprise. Transformative leaders understand that AI should not be treated as a series of isolated projects but as an interconnected ecosystem that enhances decision-making and operational efficiency.
The Amoeba Approach to AI Implementation, as discussed in my previous work, advocates for deploying AI holistically rather than creating isolated use cases. This interconnected strategy ensures that AI solutions evolve alongside corporate needs, fostering longterm value and continuous improvement.
Blockchain and Smart Contracts: Enhancing Trust and Efficiency
Blockchain technology has become synonymous with transparency, immutability, and decentralized control. In the corporate world, blockchain facilitates secure and transparent recordkeeping, which is essential for industries dealing with vast amounts of sensitive data. Smart contracts, operating on blockchain networks, automate contract execution without the need for intermediaries. This automation not only reduces administrative overhead but also enhances efficiency and compliance.
Many CIOs in our region have recognized the potential of blockchain to enhance transparency and reduce fraud. By integrating blockchain into supply chain management, finance, and asset tracking, leaders can build resilient systems that foster trust among stakeholders.
NFTs and the Metaverse: Redefining Digital Interaction
Non-fungible tokens (NFTs) and the metaverse are redefining how businesses engage with customers and stakeholders. NFTs, as unique digital assets, offer opportunities for brand engagement, intellectual property management, and the digitalization of realworld assets. Meanwhile, the metaverse—an interconnected virtual space—opens new avenues for immersive experiences, virtual meetings, and collaborative environments. Leaders who embrace these innovations can create new revenue streams and enhance customer engagement. For example, virtual showrooms or NFT-backed loyalty programs can significantly boost brand visibility while demonstrating a commitment to digital evolution.
Digital Twins and Predictive Maintenance
As a key component of the Fourth Industrial Revolution, digital twins leverage real-time data to create virtual replicas of physical assets. In industries such as construction and manufacturing, digital twins enhance predictive maintenance, optimize resource allocation, and support data-driven decision-making. Transformative leaders must advocate for the adoption of digital twins to improve operational visibility and performance.
Quantum Computing: Unleashing Unprecedented Computational Power
As the next frontier of computational technology, quantum computing holds the potential to revolutionize industries by solving complex problems that are beyond the reach of classical computers. Transformative leaders must be prepared to leverage this powerful technology to gain a competitive advantage. Quantum computing has the ability to optimize logistics, enhance cryptographic security, and accelerate research and development processes. With IBM’s latest developments on the horizon, quantum computing is no longer a futuristic concept but an imminent reality.
One of the most promising applications is in data analysis and cryptography. With the capability to process vast amounts of data simultaneously, quantum algorithms can decipher complex patterns and optimize decision-making. For corporate leaders, understanding and investing in quantum technologies now could yield significant long-term benefits.
Integrating quantum computing with AI and blockchain could also open new avenues
for secure and efficient data management, particularly in financial services, supply chain optimization, and research-intensive sectors. However, given the nascent state of quantum computing, transformative leaders must be mindful of potential risks and ethical implications associated with its adoption.
Cultivating a Forward-Thinking Culture
As human roles become increasingly critical, corporate culture can either hinder multimillion-dollar transformation projects or facilitate initiatives and help embrace the results. A transformative leader’s success is rooted in cultivating a forward-thinking culture where digital literacy and innovation are embraced as core values. Innovation labs can foster an entrepreneurial culture within corporations, while training programs that upskill employees in emerging technologies are essential. Moreover, fostering a mindset that prioritizes problem-solving and agile responses to challenges is crucial for maintaining competitiveness.
Conclusion:
The Fourth Industrial Revolution demands leaders who are not only technologically adept but also visionary and adaptable. By embracing transformative leadership, organizations can navigate the complexities of blockchain, NFTs, smart contracts, the metaverse, quantum computing, and AI to achieve sustained success. As we look ahead, the convergence of these technologies will continue to shape the corporate landscape, and leaders who proactively position their organizations at the forefront of innovation will undoubtedly thrive.
How Security Teams Stay Agile in a Rapidly Evolving Field
Bradley Schaufenbuel
Vice President and Chief Information Security Officer, Paychex
Bradley J. Schaufenbuel is currently Vice President and Chief Information Security Officer at Paychex. He has over 28 years of information security experience, the last 19 in leadership roles, at companies within the financial services and technology industries. Bradley has authored multiple books and professional journal articles about information security and IT governance. He is a licensed attorney and a member of the United States Supreme Court Bar. Bradley holds twenty-five professional designations in the areas of information security management, IT compliance, information privacy, fraud examination, IT audit, computer forensics, ethical hacking, business continuity planning, project management, cloud security, and process improvement. He holds an MBA from DePaul University and a JD and an LLM in information technology and privacy law from the University of Illinois at Chicago’s John Marhsall Law School. Bradley has served as a director on several boards, is a frequent speaker at industry conferences, is regularly quoted by the press, and has served numerous clients as a freelance consultant. He was named the Chicago CISO of the Year in 2018 and as one of the Top 100 CISOs for 2023 by Cyber Defense Magazine.
In a recent interview with CIO Magazine, Bradley J. Schaufenbuel discussed his experience with AI and cybersecurity. He shared his views on the cyber intelligence landscape, cybersecurity strategy, technological shifts, and many more.
The role of AI in cybersecurity is growing rapidly. How do you see AI and machine learning reshaping the cyber intelligence landscape today?
Artificial intelligence is being leveraged by attackers and defenders. Attackers are using AI to craft better phishing e-mails and deepfakes that improve the effectiveness of social engineering. Defenders are using AI to improve the efficacy of detection and to automate manual processes in the areas of security operations, vulnerability management, and identity and access management. Like any innovative new technology, a race has ensued to determine who can leverage AI to their advantage faster.
What are some of the most exciting or promising use cases of AI you've seen in proactive threat detection and response?
In the area of threat detection, AI models are being leveraged to detect deviations from norms that may indicate the activity of attackers. The efficacy of that technology is improving daily. In the area of response, AI SOC analysts are executing incident response playbooks that once could only be performed by human beings, and at machine speed. These developments are driving down both the mean time to detect cyber attacks and the mean time to respond to those attacks.
With cybercriminals also leveraging AI, how can security teams stay ahead in this intelligence arms race?
Security teams must embrace artificial intelligence (and quickly), as adoption of AI by defenders is the only way to keep up with the adoption of AI by attackers. This means that security teams of all
sizes and in all industries must keep themselves educated on developments in AI and invest in AI-powered security solutions where possible. Since attackers focus their efforts on the weakest targets, security teams don’t need to be first in implementing AI capabilities, but they cannot afford to be laggards.
In your experience, what are the biggest misconceptions companies have about integrating AI into their cybersecurity strategy?
In my experience, the biggest misconceptions organizations have about integrating artificial intelligence into their cybersecurity strategy is that it is too difficult or too costly. Almost all cybersecurity solution providers are adding AI capabilities to existing tools. In many cases, a security team merely needs to enable this functionality and leverage the skills they have already acquiring using tools like ChatGPT. There are numerous open-source securityrelated AI models that, with a little effort, can be leveraged at no cost.
What skills or mindsets do you think are critical for the next generation of cybersecurity professionals working with AI?
The mindset that I believe is always critical for cybersecurity professionals is one that embraces continuous learning. Since artificial intelligence will be a foundational element of most cybersecurity solutions in the future, I would suggest that every cybersecurity professional study how AI models of different types, e.g., machine learning models, foundational models, large language models, small language models, etc. are created, trained, tuned, and inferenced.
How do you ensure your teams stay adaptable and forward-thinking when both the threat landscape and the technology toolkit are constantly shifting?
I ensure my teams stay adaptable and forwardthinking in the face of a constantly changing threat landscape and security toolkit by embracing
curiosity, encouraging continuous learning, and by allocating time to “look around corners” and experiment with new technologies. I also like to engage in design partnerships with cybersecurity startups, giving my team access to the most innovative cybersecurity technologies that are being built before they are commercially available.
You've seen and led through incredible technological shifts—what leadership lessons have stuck with you the most?
YOU ARE NEVER TOO OLD OR TOO EXPERIENCED TO LEARN SOMETHING NEW, ESPECIALLY IN A FIELD LIKE CYBERSECURITY THAT IS CONSTANTLY CHANGING
The three leadership lessons that have stuck with me the most are the following. 1) Embrace diversity. Teams composed of people with a variety of perspectives are more innovative and make better decisions. 2) Practice servant leadership. You are there to inspire and support your people and not to tell them what to do. 3) Never stop learning. You are never too old or too experienced to learn something new, especially in a field like cybersecurity that is constantly changing.
What advice would you give to someone just entering the field today, hoping to work at the intersection of AI and cybersecurity?
The advice that I would give to someone just entering the field today is to make sure you have mastered the cybersecurity basics, i.e., the CIA triad, zero trust architecture, the key domains in the field (e.g., cryptography, IAM, security operations, GRC, application security, network security, etc.), and then learn as much about artificial intelligence as you possibly can. Read about or get trained in data science. Download and experiment with open-source models. Etc. Apply the knowledge to help stand out from the crowd.
THE ACCELERATION OF THE DIGITALIZATION JOURNEY – AI AS A BOOSTER
Alexander Graf
CIO, HUBER+SUHNER
Alexander Graf is CIO at HUBER+SUHNER, a Swiss-based high-tech manufacturing company.
HUBER+SUHNER, with the vision of Connecting – today and beyond, is committed to addressing the immediate connectivity needs of people while contributing to shaping the future through innovative solutions.
HUBER+SUHNER serves the three main markets of industry, communication, and transportation with applications from three technologies: radio frequency, fiber optics and low frequency. With 30 years of experience as an executive in global enterprises, Alex has always been keen to understand, explore and deploy technology, converting it into business value.
For more than 25 years, Digitalization has changed everything. The way we work and the way we live is totally different from what it was before. The invention of digital technology and its application to our daily life is mind-blowing. Just imagine to put someone into a timemachine and accelerate them fast-forward from 1970 to 2025 – how different life has become.
Obviously, Digitalization is a continuous change process, and due to the deep impact of digital innovation and rapid application of such technologies, something that can hardly be managed within corporate frameworks of line-organizations, governing bodies or project time-frames.
And now, into this already challenging business environment, AI has emerged at the heart of Digitalization and is likely to disrupt everything we tried to manage so carefully. Platforms, applications, UI, Data-Infrastructure and even human (user) behaviour will never be the same again.
Does this mean that it is time to relax and let AI run the Digitalization programs we have all been engaged in? After all, does not AI help us everywhere in decision making, code development, text generation and all those tasks we “digitalized” with high efforts and a lot of investments?
Listening to the continuous “hyperstories” of experts, marketing-teams and social media influencers, it is just a matter of time until “agents” take over and we can all concentrate on “strategy” … and maybe gardening.
Don’t get me wrong, I do believe that AI will be a great relief in many day-to-day tasks and beyond. Agents will help us to perform better and faster as a company. But it is also very
clear that if you want to grasp the benefits of AI, you need to act now and implement AI into your Digitalization efforts – and welcome it as a booster.
Everything starts with data
“Data is the new oil.” Many of us may know this phrase from Clive Humby, dating back to 2006 and thus to the first “peak” of Digitalization just before the launch of the iPhone a year later.
And it is perfectly true that all Digitalization efforts need data to become reality. And the better understood, structured and applied data is, the more likely it is to succeed with a “digital” project. Companies in highly regulated or globally operating industries put a lot of effort into managing data in order to secure data protection, data processing or to fulfil compliance needs. Thus, the framework of “data governance” is already established in many companies and this set-up is also needed to utilize data for AI applications. In the end of the day, an AI-based “assistant” and its underlying LLM relies on (public or enterprise) data as much as an ERP system does on its data in generating a production order – with the important difference that the output can easily be judged as either wrong or right in ERP but could be “hallucinated” in AI. Thus, understanding and training of data and output in AI-based applications needs special attention and a human “scholar” to make the AIassistant work correctly. This example is a good reference to the importance of data governance and therefore to lay the foundation of a successful application of AI. The good news is that AI can indeed also be used to massively enhance data quality and ensure data governance – which means that we can roll-out all (also non-AI based) Digitalization projects faster and easier.
UNDERSTANDING AND TRAINING OF DATA AND OUTPUT IN AI-BASED APPLICATIONS NEEDS SPECIAL ATTENTION AND A HUMAN “SCHOLAR” TO MAKE THE AI-ASSISTANT WORK CORRECTLY
People are people
It’s all about humans, in the end. Digitalization and AI have another common nominator, the desire to automate processes as much as possible and thus make them more efficient and effective without the costly interference of humans.
The impact of automation on humans can be twofold. Either work is “assisted” by automation (humans just have to confirm an automatically created output) or it is replaced. And both aspects have a massive impact on “us”. Yes, work (and life) is made easier and automation of processes greatly supports a more convenient work environment, to the extreme that “we”
are not needed anymore to carry out the work. Think about robots (manufacturing) or agents (AI-based “assistants”).
This leads to the ethical consideration of Digitalization and, consequently AI. The higher the degree of Digitalization and thus automation of processes, the more likely it is to substitute human work. And the comparison with robots in a manufacturing process gives the best example of the impact of automation in this respect. GenAI brings this to the next level: even realtime decision making is possible given the vast amount of data available to make decisions based on facts and considerations of alternatives. AI
THE DEGREE
OF DIGITALIZATION
REACHED A NEW LEVEL WITH THE APPLICATION OF MOBILE-DEVICE BASED USER INTERFACES, AND I AM CONVINCED THAT “AI AS A UI” WILL PUSH THIS EVEN FURTHER
agents will be used to interact autonomously and also start conversations and communication to each other and resonate on the possible outcome of a decision-making process. Are we exploring the limits of human consciousness? Although it is premature to predict the outcome, this prospect is both intriguing and somewhat unsettling.
How to boost your Digital Journey with AI
“Every process that can be digitalized will be digitalized in the end.” This phrase has been used extensively by tech/business consultants, and it has also come true in many ways. The degree of Digitalization reached a new level with the application of mobile-device based user interfaces, and I am convinced that “AI as a UI” will push this even further. Given that GenAI has some of its roots in natural-language understanding (NLU) and can do the same with almost any form of graphical input, it is very clear that we will interact more intuitively and conversationally with AI-based interfaces. The barrier to use more sophisticated applications will be further lowered, and as we have seen before, “assistants” and “agents” will execute tasks on behalf of humans. In order not to lose competitiveness, we have to adapt to these technologies, and the same race that happened with the introduction of the first computers, robots, the internet, or lately the mobile device, will start again. Either you adapt or you are out of business. Since the capability of AI is evolving fast, it is not easy to define the “right” timing for adaption. But with the availability of embedded AI features in enterprise software (Copilot-like functions) and the development of ready-to-use agents, the time to act is now.
Alasdair Redmond
Chief Information Officer, Endava
AI and Digital Friction: Overcoming Resistance to New Technologies in the Workplace
Alasdair Redmond is the Chief Information Officer at Endava, recognised in the UK CIO 100 for driving digital transformation in the education sector. With a law degree from UCLan and executive education from Harvard Business School, he brings a strategic, business-led approach to technology. Before joining Endava, Alasdair was a Board Member and Technology Director at Intuitus, where he oversaw over 400 technology due diligence projects and post-deal value creation. Earlier in his career, he led global IT services and solutions at Convergys, a $2bn BPO, delivering technology and digital services to Fortune 100 clients. He has also held leadership roles in consultancy and systems integration. Passionate about building high-performing teams, Alasdair continues to shape technology strategies that drive innovation, efficiency, and sustainable value in a rapidly evolving digital landscape.
In a recent interview with CIO Magazine, Alasdair Redmond discussed his experience with technology and digital advice. He shared his views on technology and digital transformation, integrating AI, exciting trends in AI and digital transformation, and many more.
TO PROACTIVELY COMBAT ANY DIGITAL FRICTION CONCERNS, BUSINESS LEADERS SHOULD INTRODUCE TRAINING SESSIONS FOR EMPLOYEES AND START WITH EASY-TO-USE TECHNOLOGY THAT FEEDS INTO COMPANY GOALS AND SIMPLIFIES WORKFLOWS
How is AI reshaping digital transformation strategies across industries, and what are some of the most significant advancements you've seen?
As with any emerging technology, it’s been fascinating to witness AI drive change across industries, revealing opportunities that were unimaginable just a few years ago.
In healthcare, we recently worked with SOPHiA GENETICS, a software company that leverages AI to advance cancer and rare diseases research and treatment. Recognising that modernised IT infrastructure was key to improving user experience, they called on us to mitigate platform inefficiencies, optimise their IT service management tool, and refine internal workflows. The impact of this is a stronger foundation that empowers researchers, accelerates breakthrough and ultimately, saves lives.
It was a similarly inspiring story with the English National Opera who devised a form of singing therapy for patients with long Covid, turning to us to scale the programme and help thousands of sufferers at once.
In the payments space, we’ve been working with a global B2B payments company to create a cloud-based platform that saves them money and provides an improved customer experience. With rising consumer expectations, companies using AI to differentiate themselves are prioritising personalisation. I expect this shift will be significant in raising standards across industries in years to come.
And this is just the tip of the iceberg. Advancements in AI are making waves across all industries, and the value add for individuals, business, and society, is only going to grow.
What are the key challenges organizations face when integrating AI into their digital transformation roadmap, and how can they overcome them?
A fundamental issue that we see companies facing as they embrace AI is lack of access to strong data, without siloes or legacy technology standing in the way. I should highlight that there are ways to embrace AI without a databased, modern infrastructure; at Endava, we’ve seen the direct impact of AI’s capabilities when working with smaller data sets, from analysing documents to placing checks on back-end processes. However, without full understanding of their core data assets, it becomes difficult for companies to experience the full value of AI. To overcome this, companies can begin their digital transformation journey by analysing and modernising their core systems, creating a solid, data-based foundation to support with the integration of emerging technologies.
Another key challenge with AI adoption is digital friction, where employees struggle to work with new technologies, leaving a lasting impact on company productivity. To proactively combat any digital friction concerns, business leaders should introduce training sessions for employees and start with easy-to-use technology that feeds into company goals and simplifies workflows.
With AI playing a greater role in decision-making, how can organizations ensure ethical AI usage and mitigate risks related to bias and transparency?
Agentic AI can enhance transparency in these scenarios. Despite regulations already in place,
it’s understandable for both companies and workers to be apprehensive about changing entire workflows as they embrace AI. Agentic AI doesn’t operate solely within a ‘black box’ like regular AI systems. Instead, data can be recorded and presented in a way readable by the user, acting as a layer of reassurance for those reluctant to ‘trust the process’ or concerned about related pitfalls, like hallucinations.
This can be assured without agentic AI too. The key is to build a culture of responsibility and accountability, with organisations providing guidance and training to their employees. By proactively addressing ethical AI concerns, organisations can reduce risks over time.
At Endava we formed a cross functional AI Committee early on and this has helped to set the standards and security for responsible use of AI.
How do you see AI transforming job roles, skill requirements, and workplace dynamics in the next decade?
I believe increased AI use will lead to a boost in strategic thought. As AI tackles the more repetitive, everyday tasks, workers will be able to focus more on activities that require human input. In industries like healthcare, we’ll see more emphasis on the ‘human’ aspects of roles, improving patient care through providing medical professionals with more time for quality face-to-face interactions.
The use of AI has already driven unprecedented change across industries. I won’t claim to be able to guess what the workplace will look like in 10 years, but I’m excited to see how the increased focus on human thought and strategy drives industries forward.
What are some of the most exciting trends in AI and digital transformation that businesses should prepare for in the near future?
Agentic AI is the one to watch right now. It’s set to be impactful across industries, from banking to healthcare. Agentic AI needs less human intervention than Gen AI does, making it easier for businesses to scale operations and align progress with company goals. For encouraging stakeholder buyin, this growth potential will be a key selling point.
With a recent study from Microsoft highlighting a fundamental gap between companies embracing AI and those without a strategy in place, now is the time to be curious. Through talking to experts and exploring how agentic AI is impacting industries, leaders can learn how the technology’s capabilities will be best suited to improving efficiency and meeting goals in their organisation. Those that don’t risk being left behind.
What advice would you give to business leaders and professionals looking to drive AI-led digital transformation successfully?
A third of companies surveyed for The Next Wave of Digital Transformation in the Era of the AI-Powered Digital Shift cited issues with poor quality of data or poorly labelled data sets within their organisations. To combat this, transformation should begin at the foundation of any technology stack, the core; modernising to facilitate the adoption of emerging technologies in years to come.
Through building a flexible infrastructure, enabling data to be fed into centrally located solutions, you can create a solid foundation for innovation.
It's important to note that, to bring about truly transformational change, you should feel confident discussing plans with industry experts, following their advice to inform the journey ahead. This step is especially important if their knowledge is industry specific and tailored to your corporate objectives.
Begin by considering business goals and align your adoption of solutions with them. Choose solutions that work for the company, not just those claiming to be a ‘silver bullet’. Above all, prioritise clear communication. Keep your team informed, address their concerns, and create opportunities for open dialogue.
What keeps you passionate about AI and digital transformation, and what is one lesson or philosophy that has guided you throughout your career?
Curiosity. I switched from Law to Technology early in my career and it’s been fascinating to see the challenge, impact and value of each wave of transformative technology. That value though, starts with the business opportunity or problem you’re solving and not the technology. This intersection is an interesting place to explore.
It may not be a philosophy, but I have always put people at the centre of success. Throughout my career what I’ve most valued is seeing team members grow into leaders and shape their own story. High performing teams become more than the sum of their parts and in my experience can achieve great things.
BUILDING A STRONG AI GOVERNANCE, RISK, AND COMPLIANCE (GRC) PROGRAM: A CIO-CISO COLLABORATION GUIDE
Don Cox
Chief Information Security Officer, American Public Education, Inc.
Don Cox is a seasoned cybersecurity and IT executive with over 20 years of experience driving digital transformation, risk management, and enterprise security strategy. As the CISO and VP of IT Service Management at American Public Education, Inc. (APEI), Don leads cybersecurity, compliance, and IT operations, ensuring resilience in an evolving threat landscape. A strategic leader with expertise in healthcare, product development, and logistics, he has collaborated with federal agencies on cybercrime investigations. Recognized for visionary leadership, Don is passionate about AI, innovation, and fostering a security-first culture to enable business growth and operational excellence.
The Growing Need for AI Governance, Risk, and Compliance
Artificial intelligence (AI) is rapidly transforming enterprises by automating complex processes, enhancing predictive analytics, and improving decision-making. However, AI’s expansion brings significant challenges, including data privacy risks, security vulnerabilities, regulatory compliance issues, and ethical concerns. As organizations embed AI into their core business functions, they must establish a structured AI Governance, Risk, and Compliance (AI GRC) framework to ensure that AI-driven systems are transparent, secure, and aligned with business objectives.
For a successful AI GRC implementation, collaboration between the Chief Information Officer (CIO) and the Chief Information Security Officer (CISO) is essential. The CIO is responsible for AI innovation, strategy, and integration into the business, while the CISO ensures security, compliance, and risk management. When these two executives work together, they can develop a robust AI governance structure that enables innovation while safeguarding against AI-related risks.
Aligning AI Strategy with Security and Compliance
The first step in establishing an AI GRC framework is defining a shared strategy that balances innovation with risk management. CIOs must ensure AI deployments align with business priorities, while CISOs must enforce security and compliance protocols to protect data and maintain regulatory adherence.
A comprehensive AI policy framework should be developed to define governance structures, outline AI use cases, and set clear
accountability for AI-related decisions. This framework should specify how AI models are developed, deployed, and monitored to ensure fairness, transparency, and security. Establishing a cross-functional AI governance committee that includes IT, security, legal, compliance, and business leaders will help enforce these policies, ensuring that AI initiatives support organizational objectives while minimizing security threats.
Identifying and Mitigating AI-Related Risks
AI introduces a range of unique risks, from algorithmic bias and adversarial attacks to model drift and regulatory violations. To mitigate these risks, CIOs and CISOs must collaborate to conduct AI risk assessments that evaluate vulnerabilities across the AI lifecycle. These assessments should focus on potential biases in AI models, security threats related to adversarial manipulation, and compliance risks stemming from data privacy regulations. CISOs should lead threat modeling exercises to identify potential cybersecurity weaknesses in AI applications. By integrating security measures such as data encryption, rolebased access controls, and real-time AI activity monitoring, organizations can reduce exposure to AI-driven security threats. Meanwhile, CIOs should work with IT teams to embed security and bias detection mechanisms directly into AI development workflows, ensuring that AI models remain ethical and trustworthy.
Monitoring AI decision-making processes is also critical. Organizations should establish a system that continuously evaluates AI outputs for unintended bias or anomalies. If discrepancies are detected, corrective measures
must be implemented promptly to ensure that AI remains aligned with compliance requirements and business ethics.
Ensuring AI Compliance with Evolving Regulations
As AI regulations become more stringent, enterprises must ensure their AI implementations comply with legal and industry standards. Regulatory frameworks such as the EU AI Act, NIST AI Risk Management Framework, GDPR, and other industry-specific mandates dictate how AI should be governed, monitored, and reported.
The CISO plays a vital role in overseeing AI compliance efforts, working closely with legal and regulatory teams to ensure adherence to established standards. Meanwhile, the CIO must ensure that compliance requirements are built into AI deployments from the outset, rather than being addressed after implementation.
To maintain regulatory alignment, organizations should establish a structured compliance review process that evaluates AI systems against applicable laws. AI models used for decision-making should be transparent
and explainable, allowing regulatory bodies and internal auditors to assess their fairness and legality. In addition, organizations should develop third-party risk management protocols to ensure AI vendors and partners meet the same security and compliance standards required internally.
Implementing AI Monitoring, Auditing, and Incident Response
AI governance does not end once an AI system is deployed. Continuous monitoring is essential to detect security threats, model drift, compliance violations, and operational failures. By implementing an AI performance monitoring framework, organizations can track AI systems in real time, flagging potential anomalies that could compromise their integrity.
Regular AI audits should be conducted to ensure that models function as intended. These audits should examine AI decision-making patterns, verifying that AI-generated outcomes are consistent, fair, and unbiased. The results of these audits should be reviewed by IT, security, and compliance teams, who can make necessary adjustments to maintain AI reliability.
ORGANIZATIONS SHOULD ESTABLISH A SYSTEM THAT CONTINUOUSLY EVALUATES AI OUTPUTS FOR UNINTENDED BIAS OR ANOMALIES
TRAINING
PROGRAMS SHOULD BE INTRODUCED TO HELP IT AND SECURITY TEAMS UNDERSTAND AI SECURITY RISKS, BIAS DETECTION TECHNIQUES, AND REGULATORY FRAMEWORKS
In addition to ongoing monitoring, organizations must develop an AI incident response plan that outlines how to address AI-related security breaches and compliance failures. This plan should detail procedures for identifying AI vulnerabilities, escalating security concerns, and implementing remediation strategies. A well-structured response plan will enable enterprises to swiftly address AI failures while minimizing operational disruptions.
Building an AI-Responsible Culture
Ensuring that AI is used responsibly across the enterprise requires a culture of awareness and accountability. CIOs and CISOs should work together to educate employees, business leaders, and IT teams about AI risks, ethical considerations, and compliance requirements. Training programs should be introduced to help IT and security teams understand AI security risks, bias detection techniques, and regulatory frameworks. Business leaders should also receive AI literacy training to help them make informed decisions about AI implementations.
Encouraging responsible AI experimentation can further reinforce governance best practices. Organizations should establish AI sandboxes— controlled environments where teams can test AI
models while ensuring security and compliance protocols are in place. This allows for innovation without exposing the organization to undue risks. By fostering a company-wide AI-aware culture, enterprises can empower employees to use AI responsibly while maintaining alignment with security and regulatory expectations.
Conclusion
As AI becomes increasingly integrated into enterprise operations, the collaboration between CIOs and CISOs is more critical than ever. The CIO’s role in AI adoption and innovation must be balanced by the CISO’s focus on security, compliance, and risk management. Together, these executives can build a comprehensive AI GRC framework that promotes AI-driven growth while protecting the organization from AI-related threats.
By establishing governance policies, conducting risk assessments, ensuring regulatory compliance, monitoring AI performance, and fostering an AI-responsible culture, CIOs and CISOs can ensure that AI remains an asset rather than a liability. A strong partnership between these two leaders will not only enhance AI security and compliance but will also enable organizations to leverage AI’s full potential with confidence and accountability.
