Information Week

Like many chief information officers, IBM CIO Matt Lyteson is approaching artificial intelligence both carefully and optimistically. In a recent online interview, he observed that no CIO can afford to switch focus on every new “it” thing, yet AI is certainly anything but a passing fad. “My approach to AI includes traditional AI, generative AI, agentic AI, and business automation — using any and all of these tools in concert to help transform IBM’s business into a digital operating model,” Lyteson explains. “While there are some incredible new AI capabilities, one thing hasn’t changed — it’s best to take a holistic view rather than simply deploy another tool.”  Lyteson notes that generative AI in particular has the potential to impact every business area. “Out of the box it can often be a blunt tool — a sledgehammer for the work of a chisel.” To gain full value out of generative AI, he believes that new adopters should focus on the specific business areas that are ripe for transformation.  An Initial Project  Lyteson’s first AI project was deploying generative AI, trained on the firm’s own data, to the entire employee population, and doing so in a secure, trusted way. “We already had a number of AI-powered assistants and automations, and users were familiar with these for specific tasks or functions,” he explains. While relatively simple and uncomplicated, the new project represented a significant step forward, providing a general, enterprise-wide solution with context-specific generative capabilities.  Related:EY Americas Consulting’s CTO Noel on Getting Close to Innovation Matt Lyteson The project helped Lyteson move forward on three basic goals. “First, we wanted to give IBMers a space to play — a safe, trusted, and secure environment to use and experiment with AI on our own business data,” he says. The approach was designed to minimize risk. It also helped Lyteson equip employees with a user interface that worked specifically for them. “This helped build on our cultural transformation at IBM, pointing employees toward how AI can augment their work, and signaling our expectation for this to happen day-to-day in every corner of the business.”  The approach, Lyteson notes, also established an important reference point for future expansion. “We’ve introduced additional assistants and agents since then [yet] it remains the single-entry point for employees looking to access the continually expanding knowledge and capabilities we’re rolling into the back-end technology.”  Effective Planning  Successfully implementing AI demands thoughtful intentionality at the outset, Lyteson says. “Our plan began with getting key stakeholders around a table and zeroing-in on crystal clear objectives,” he explains. “We didn’t allow for mission creep, and we also didn’t dive into complex environments with no specific plan.”  Related:Tech Company Layoffs: The COVID Tech Bubble Bursts Lyteson says project planning began in November 2023 and was completed in less than 90 days, resulting in the first iteration’s release. “Because the capabilities of the technology keep evolving, as does our acumen, we continue to iterate based on feedback and solving specific needs,” he notes. “For example, routing between different assistants.”  Expectations Met  Lyteson says that in many respects the project was about showcasing the incredible potential of generative AI to the full breadth of IBM’s employee — more than 200,000 team members doing all sorts of work worldwide. “That was a key first step to having AI be an enabler, and we have now deployed more and more AI-powered agents and business automations across the enterprise.”  “Thanks to an upfront commitment to intentionality, our project met initial expectations, and we’ve been able to continually learn and iterate since then,” Lyteson says. “A CIO’s work is a team sport, especially at large companies.”  Lyteson notes that it was also interesting to see how generative AI often spits out nondeterministic answers when some business functions absolutely require deterministic responses. “This was a key learning for us,” he says. “As a result, we took steps to help our various user bases understand [the concern] — proactively communicating, offering education sessions, and most importantly embedding the right messaging within the user interface itself.”  Related:How to Hold Efficient Team Meetings A Final Thought  A single project such as this one should be table stakes for CIOs, Lyteson says. “Learning to initiate AI projects, experiment rapidly, and capitalize on data-backed learnings is key to ongoing success,” he observes. “This was a nice example of all of those elements rolled into a single package.”  source

A global survey of 600 IT leaders highlights this concern, revealing that while the potential of Gen AI to transform work is widely recognized, the digital infrastructure in most organizations simply isn’t ready. This isn’t about minor tweaks; it’s about a fundamental need to rebuild. Even though 79% of IT leaders believe Gen AI has the potential to elevate the quality of work, fewer than half think their current digital workplace tools effectively support productivity, engagement, and innovation. 89% agree that only a foundational overhaul of digital infrastructure will enable Gen AI to truly deliver on its promise. This insight from Lenovo’s Work Reborn Research Series 2025, identifies both the opportunities and the critical challenges presented by Gen AI and highlights an urgent need for IT transformation. In order to realize Gen AI’s true value, organizations must rethink their operational frameworks, starting with their technology infrastructure. The Urgent Need for IT Transformation The need for IT transformation becomes clear when we consider the many opportunities Gen AI affords. This isn’t just another software upgrade; it’s a catalyst to redefine how teams collaborate, ignite creativity, and boost their productivity. Imagine breaking down global communication barriers with instant translations, freeing skilled employees from repetitive work to focus on groundbreaking ideas and streamlining complex processes with intelligent automation. Related:Navigating Generative AI’s Expanding Capabilities and Evolving Risks It’s no surprise that nearly half (49%) of IT leaders see improving the employee experience as a top priority. In fact, according to the 2025 CIO Playbook: It’s Time for AI-nomic’s, enhancing productivity is the leading business goal for organizations in 2025. However, the report also highlights significant hurdles faced by IT teams, particularly in delivering personalized experiences and automating IT support. While the majority of IT leaders (63%) understand the importance of a tailored digital workplace, the lack of adaptable tools leaves many organizations struggling to unlock productivity with a one-size-fits-all approach. And despite 61% recognizing the value of Gen AI-driven IT support, the actual implementation remains a challenge. The answer isn’t a simple patch; it requires a complete architectural shift. Gen AI needs to be embedded at the very core of a workplace IT strategy. When integrated seamlessly, AI can intuitively understand individual employee needs, automatically configuring their tools and workflows. Picture AI-powered IT support that anticipates and resolves issues before they even impact productivity. Related:How Companies Are Making Money from AI Projects To realize these gains, proactive change is needed. While Gen AI offers the potential to free up teams to focus on strategic innovation, it also gives organizations a chance to set themselves apart from the rest. In fact, 76% of IT leaders say that businesses not empowering employees with AI will lag in the next one to two years. Three Steps to an AI-Ready Workplace I believe IT leaders are at a pivotal moment, but they must move beyond incremental gains and strategically weave Gen AI into the heart of their organizations. This demands a strong partnership with executive peers, a shared vision, and the courage to lead significant change. “Reinventing Workplace Productivity” outlines three critical steps on this journey: 1. Simplify and Personalize the Employee Experience: Tailor digital tools, workflows, and applications to individual roles and working styles, enabling employees to leverage Gen AI for maximum productivity and innovation. 2. Automate IT Processes with AI: Utilize Gen AI to manage workplace devices and IT support, freeing up resources for higher-value tasks and ensuring seamless operations. 3. Transform Workflows for Value Creation: Re-engineer existing workflows and processes to fully realize the capabilities of Gen AI and drive innovation. Related:How to Avoid the AI Customer Experience Cliff By prioritizing personalization, intelligent automation, and reimagined workflows, companies can build a workplace that truly unlocks the potential of Gen AI. The Work Reborn Research Series 2025 is just getting started. Building a Gen AI-driven future requires strong leadership and a willingness to rebuild. Are you ready to take the necessary steps? source

Today’s tech leaders must simultaneously navigate nonstop change on all fronts from cloud shifts and AI disruption to rising security threats. To reveal important insights that only real-world experience can forge, InformationWeek is reaching out to top CIOs about what they’re facing now, how they’re handling it, what advice they have for aspiring chief information officers, and how they got where they are.   These conversations aren’t just about tools and platforms. Every aspect of a seasoned tech leader’s experience is touched on from their business strategy and leadership approach to the real-world lessons that come from building resilient tech organizations when the world itself seems to morph beneath their feet.  Today we’re talking with Gill Haus, managing director and CIO at Chase, the consumer and community banking division of JPMorgan Chase & Co. Haus leads one of the largest and most complex tech operations in financial services, where he’s focused on scaling innovation, modernizing legacy systems, and keeping millions of customers connected and secure every day.  Here is what he had to say.  What has your career path looked like so far?  I always knew I wanted to work in technology. Even in middle school and high school, my evenings were spent watching science fiction, eating pizza, listening to electronic music, and coding. I realized early in my career that I enjoyed solving problems and helping others solve problems together. This has been a self-fulfilling prophecy and enabled me to get the roles I’ve had in my career. I didn’t set out to become the CIO for Chase; I focused on solving problems, helping people around me, and learning, and that paved the way for the roles I held.  Related:Tech Company Layoffs: The COVID Tech Bubble Bursts What are the highlights of your career path?  I’ve had the chance to work with some amazing tech brands like eBay, PayPal, Capital One, and JPMorgan Chase. Each experience has been unique, but a standout moment was during the pandemic at Chase. We supported millions of small businesses through the Paycheck Protection Program. It was tough, with long nights, but the teamwork and positive impact were incredibly rewarding.  I’m also proud of modernizing our flagship chase.com website and mobile app, moving them fully to the cloud. Things move quickly here, and in the past few years of rapid transformation, every day feels like a highlight. We serve millions of customers, helping them achieve their dreams and goals through the ongoing modernization of our technology.  What are you excited about in your current role?  Related:How to Hold Efficient Team Meetings I’m thrilled to influence and steer the technology direction of a firm that touches people, businesses, corporations, and governments globally. The technology challenges at our scale are second to none, and it’s exciting to work at the heart of the economy, where money plays a central role in people’s lives. It’s exhilarating to be part of a place where we can deploy technologies — from cloud to mobile to generative AI — to millions of customers. Despite being a large company, our people make it feel like a small family, making it enjoyable to come to work every day.  Please tell us about your advocacy efforts for diversity, inclusion, and culture.  Everyone brings their own unique insights and perspectives, offering fresh ways of thinking. It’s important to tap into this dynamic, which is why we aim to attract the best and brightest from around the world to JPMorgan Chase. I make sure everyone’s voice is heard, including junior employees, by involving them in discussions like monthly business reviews, so they can learn and contribute. We foster a meritocracy where you can be yourself and thrive.  What emerging trends are you excited about in the industry?  I’m excited about the promise of generative AI tools and how they will likely compel teams to focus on the fundamentals, offering benefits beyond just writing software. These tools can generate code and reduce engineer toil, but they also emphasize the importance of foundational computer science principles. By addressing the time-consuming and error-prone processes that have slowed us down — through unit testing, component testing, end-to-end testing, performance testing, and software release — and focusing on automating these areas, we can adopt generative AI more easily. This focus will help us use these tools to solve complex problems quickly and with greater confidence. A fully automated end-to-end software delivery lifecycle is crucial for scaling these technologies, allowing engineers to focus on the right tasks and boost productivity.  Related:5 Smart Hardware Moves CIOs Are Making During Tariff Uncertainty What do you do for fun or to relax?  I’ve loved electronic music and computers since I was a kid, and that hasn’t changed. In my spare time, I dive into coding and check out the latest tech. I still DJ and hit the clubs now and then, because embracing what makes us happy is key to recharging. This balance helps me bring my best to work, sparking creativity, and getting things done effectively.  What advice do you want to give to young people considering a leadership path in IT?  Embrace curiosity and welcome change because change is unstoppable. Leaders who cherish change and guide others through it are rare, but they are our future leaders, especially as change accelerates. If you’re feeling scared, that’s a good sign — it’s a part of learning. Embrace the healthy dose of fear that comes with growth every day.  source

Ask technologists and enterprise leaders what they hope AI will deliver, and most will land on some iteration of the “T” word: transformation. No surprise, AI and its “cooler than you” cousin, generative AI (GenAI), have been hyped nonstop for the past 24 months.  But therein lies the problem.  Many organizations are rushing to implement AI without a grasp on the return on investment (ROI), leading to high spend and low impact. Without anchoring AI to clear friction points and acceleration opportunities, companies invite fatigue, anxiety and competitive risk. Two-thirds of C-suite execs say GenAI has created tension and division within their organizations; nearly half say it’s “tearing their company apart.” Most (71%) report adoption challenges; more than a third call it a massive disappointment.  While AI’s potential is irrefutable, companies need to reject the narrative of AI as a standalone strategy or transformational savior. Its true power is as a catalyst to amplify what already works and surface what could. Here are three principles to make that happen.  1. Start with friction, not function  Many enterprises struggle with where to start when integrating AI. My advice: Start where the pain is greatest. Identify the processes that create the most friction and work backward from there. AI is a tool, not a solution. By mapping real pain points to AI use cases, you can hone investments to the ripest fruit rather than simply where it hangs at the lowest.  Related:Navigating Generative AI’s Expanding Capabilities and Evolving Risks For example, one of our top sources of customer pain was troubleshooting undeliverable messages, which forced users to sift through error code documentation. To solve this, an AI assistant was introduced to detect anomalies, explain causes in natural language, and guide customers toward resolution. We achieved a 97% real-time resolution rate through a blend of conversational AI and live support.  Most companies have long-standing friction points that support teams routinely explain. Or that you’ve developed organizational calluses over; problems considered “just the cost of doing business.” GenAI allows leaders to revisit these areas and reimagine what’s possible.  2. The need for (dual) speed  We hear stories of leaders pushing an “all or nothing” version of AI transformation: Use AI to cut functional headcount or die. Rather than leading with a “stick” through wholesale transformation mandates or threats to budgets, we must recognize AI implementation as a fundamental culture change. Just as you wouldn’t expect to transform your company culture overnight by edict, it’s unreasonable to expect something different from your AI transformation.  Related:How Companies Are Making Money from AI Projects Some leaders have a tendency to move faster than the innovation ability or comfort level of their people. Most functional leads aren’t obstinate in their slow adoption of AI tools, their long-held beliefs to run a process or to assess risks. We hired these leaders for their decades of experience in “what good looks like” and deep expertise in incremental improvements; then we expect them to suddenly define a futuristic vision that challenges their own beliefs. As executive leaders, we must give grace, space and plenty of “carrots” — incentives, training, and support resources — to help them reimagine complex workflows with AI.  And, we must recognize that AI has the ability to make progress in ways that may not immediately create cost efficiencies, such as for operational improvements that require data cleansing, deep analytics, forecasting, dynamic pricing, and signal sensing. These aren’t the sexy parts of AI, but they’re the types of issues that require superhuman intelligence and complex problem-solving that AI was made for.  3. A flywheel of acceleration  The other transformation that AI should support is creating faster and broader “test and learn” cycles. AI implementation is not a linear process with start here and end there. Organizations that want to leverage AI as a competitive advantage should establish use cases where AI can break down company silos and act as a catalyst to identify the next opportunity. That identifies the next as a flywheel of acceleration. This flywheel builds on accumulated learnings, making small successes into larger wins while avoiding costly AI disasters from rushed implementation.  Related:How to Avoid the AI Customer Experience Cliff For example, at Twilio we are building a customer intelligence platform that analyzes thousands of conversations to identify patterns and drive insights. If we see multiple customers mention a competitor’s pricing, it could signal a take-out campaign. What once took weeks to recognize and escalate can now be done in near real-time and used for highly coordinated activations across marketing, product, sales, and other teams.  With every AI acceleration win, we uncover more places to improve hand-offs, activation speed, and business decision-making. That flywheel of innovation is how true AI transformation begins to drive impactful business outcomes.  Ideas to Fuel Your AI Strategy  Organizations can accelerate their AI implementations through these simple shifts in approach:  Revisit your long-standing friction points, both customer-facing and internal, across your organization — particularly explore the ones you thought were “the cost of doing business”  Don’t just look for where AI can reduce manual processes, but find the highly complex problems and start experimenting  Support your functional experts with AI-driven training, resources, tools, and incentives to help them challenge their long-held beliefs about what works for the future  Treat AI implementation as a cultural change that requires time, experimentation, learning, and carrots (not just sticks)  Recognize that transformation starts with a flywheel of acceleration, where each new experiment can lead to the next big discovery  The most impactful AI implementations don’t rush transformation; they strategically accelerate core capabilities and unlock new ones to drive measurable change.  source

According to a McKinsey survey, 61% of executives feel that at least half of the time they spend making decisions — much of it in meetings — was ineffective. Just 37% of respondents said their organizations’ decisions were both timely and high quality.  When it comes to creating effective and efficient meetings, preparation matters, says Peter Wood, CTO at tech recruitment firm Spectrum Search. He believes that the most high-quality and results-focused IT team meetings always start with one thing: clarity. “Everyone knows why they’re there, and that sets the tone for the entire session,” Wood explains in an online interview. “If you can’t sum up the purpose of the meeting in a single sentence, it’s probably not ready to happen.”  Justin Maynard, a vice president at IT consulting firm Resultant, stresses the need for detailed advance planning. “All of the normal things that characterize an efficient meeting need to be in place — clear objectives, an agenda shared in advance, and active engagement are all needed,” he says in an email interview.  Building Efficiency  Limit meeting participants to necessary stakeholders, advises John Russo vice president of healthcare technology solutions at healthcare software provider OSP Labs. He believes that meetings should be short, focused, and outcome driven. “We respect time by sticking to priorities and reserving discussions for items that truly require group alignment,” Russo says in an online interview. “It’s all about purpose and preparation.”  Related:5 Smart Hardware Moves CIOs Are Making During Tariff Uncertainty Russo says this approach works well, since it encourages participants to arrive prepared, allowing decisions to be made faster with a sense of accountability. “Especially in healthcare IT, where time is critical, this structure ensures meetings aren’t just check-ins — they’re strategic tools that drive momentum without wasting energy.”  Every meeting should have a clear reason to happen — whether it’s syncing up on a sprint, solving a specific problem, or aligning priorities, says Trevor Young, chief product officer at security and compliance specialist Security Compass. “Send out an agenda ahead of time so attendees can come prepared,” he advises in an email interview. “Don’t invite the whole world — just the folks who really need to be there.”  Wood stresses the importance of valuing participants’ time. “Most engineers I’ve worked with dread meetings that drag on or don’t lead to any actionable outcomes,” he says. “If everyone leaves the meeting knowing exactly what they need to do, or with a clear understanding that nothing has changed, then the meeting has done its job.”  Related:How CIO Kristy Folkwein Is Building an IT Team for ADM’s Digital Future Stay focused, Maynard recommends. “IT people always want to dig into the details and solve every issue,” he says. This can result in meetings that fall into a bottomless rabbit hole. “While you may solve one problem, you have wasted everyone else’s time.” Arranging a direct connection with the individuals best suited to solve the issue makes more sense.  Costly Mistakes  Trying to control every meeting aspect is a common trap, Russo says. “Leaders who dominate the conversation miss out on valuable input.” Also, holding meetings just for routine’s sake builds no value. “Empowering the team and knowing when not to meet is often more impactful.”  One of the biggest mistakes leaders make is assuming that speaking relentlessly means making an impact, Wood says. He believes that many meeting moderators talk too much. Meetings shouldn’t be a platform for long, windy monologues. “You’re there to diagnose, not lecture.” Asking the right questions and then listening is key. “Engineers, for instance, don’t need to be micromanaged — they need to feel trusted to tackle problems,” he states. “The way you run your meetings should reflect that trust.”  Related:The Pros and Cons of Becoming a Government CIO One simple rule is to avoid wasting time, Wood says. If a meeting doesn’t lead to any progress, end it. “This approach forces you to treat every meeting as something valuable and ensures that you’re always focused on moving forward.” He also recommends rotating meeting leaders, including giving junior team members a chance to offer their views. “This encourages ownership and brings in new perspectives.”  Closing Thoughts  You’ll feel it when a meeting drags, Young says. “People are zoning out, multitasking, or asking the same questions as last week.” If meetings always run long, lack clear outcomes, or leave participants wondering what to do next — it’s not doing its job. Additionally, if a participant says, “This could have been handled by email,” it’s a clear sign that the meeting was probably unnecessary.  Make reflection part of the process, Russo suggests. Regularly ask the team what’s working, involve all parties, and keep meetings dynamic. “A quick check-in every few weeks will prevent drift and reinforce a culture in which everyone values time and focus.”  source

Ongoing trade tensions and shifting tariffs have left CIOs in a tough spot: how do you maintain stability while controlling costs? With the price of exports surging as companies rush to purchase before tariffs hit harder, reactive stockpiling is no longer sustainable.  In uncertain times, having a clear picture of your technology assets and how they’re being used becomes a powerful edge. Strategic CIOs take inventory, identify inefficiencies, and make every dollar count.  Start with Visibility: Know What You Own Before making new purchases, it’s essential to understand what’s already in your environment. Many organizations still track IT assets in spreadsheets, leading to inaccuracies and waste. A proper inventory system reveals opportunities to redistribute and repurpose hardware rather than overspend.  One of the organizations I’ve worked with quickly reassessed its technology assets upon anticipating new tariff laws. Their solution? They extended hardware upgrade cycles and provided refurbished devices to new hires. Simple changes that maintained productivity while significantly reducing costs.  Beyond budgeting concerns, poor asset visibility also introduces operational risks. Unused devices can lead to unmonitored endpoints, outdated software, or missed security patches. Visibility isn’t just a cost saver; it’s also a safeguard against compliance gaps and cybersecurity threats.  Related:How to Hold Efficient Team Meetings When you know what’s in use, underused, and outdated, you can prioritize purchases based on actual need, not fear.  5 Moves to Strengthen Your Hardware Strategy Forward-thinking CIOs are adopting these five tactics to build flexibility and resilience:  Extend Hardware Lifecycles Use predictive monitoring to catch failures before they happen. This allows for planned replacements, avoids emergency purchases, and squeezes more value from every asset.  Unite IT and Finance Data When IT and finance share data, decision-makers get a clear picture of total cost of ownership. This alignment leads to smarter choices between repair and replacement.  Prioritize Mission-Critical Systems Not all systems are created equal. Identify which assets are most essential to your operations and protect that budget, while trimming less critical areas.  Reassess Vendor Agreements Tariff-driven uncertainty is the perfect time to revisit contracts. With clear usage data and a tighter strategy, you can negotiate favorable terms more easily.  Automate and Optimize Use automation to reduce manual tasks, enabling your IT team to focus on innovation while controlling operational costs.  Related:How CIO Kristy Folkwein Is Building an IT Team for ADM’s Digital Future Stay Strategic, Not Reactive Cutting all new IT projects may feel safe, but often leads to stagnation. Instead, successful CIOs are maintaining strategic momentum while tightening spending elsewhere. Hardware decisions don’t happen in a vacuum. Collaboration with finance, procurement, and operations is essential.  Planning Ahead: Build Resilience Now Looking forward, resilient organizations are diversifying suppliers, opting for modular hardware upgrades, building device pools for redeployment, and exploring cloud solutions to reduce hardware dependence. Tariff uncertainty is challenging, but it also presents a chance to innovate and optimize. CIOs who take stock, invest in visibility, and act strategically can weather the storm while positioning their organizations for long-term success. Now is the time to shift from reactive responses to resilient frameworks. A proactive hardware strategy empowers CIOs to lead with clarity, agility, and confidence in the face of global uncertainty.  source

Cybersecurity is paramount in the world of digital payments. As senior vice president and CISO at Visa, Subra Kumaraswamy leads cybersecurity efforts at the payment card services giant with a philosophy that he and his team could always be doing more.  “Every day I wake up and say, ‘What I should do better?’” he tells InformationWeek. “Being pessimistic and being paranoid, P&P, meaning constantly look at this as ‘glass half empty.’ What else we should be doing to ensure we have a strong security posture?”  Before he stepped into the lead cyber job at Visa, Kumaraswamy built his career through many different roles at many different companies. He looks back at those experiences and forward to the ever-present need to manage and strengthen cybersecurity in his current position.   A Diverse Set of Roles  Kumaraswamy considers himself an engineer and a problem solver at heart. His first job was as a software engineer at the University of Notre Dame; he was figuring out how to offer internet services across the campus before the dot com boom began.   Since that first job, he has built experience at companies like Netscape, Sun Microsystems, eBay, and Intuit. He also spent time as an entrepreneur.   “In my journey, what defined me was the diversity … of roles,” says Kumaraswamy. “I was able to be a developer. I was able to be a data center architect. I was able to run services in the cloud, and I was able to be an entrepreneur. And all of this helped me to create much more of a holistic view.”  Related:How to Hold Efficient Team Meetings When he was at Netscape, the company was hit with a DDoS attack, the initial spark that got Kumaraswamy interested in cybersecurity. Throughout his career, he has focused on securing enterprises as they ride the waves of new transformative technology, whether that be the internet, the cloud, or now, AI.   Subra Kumaraswamy He was working as head of digital security at Apigee, a company that is now part of Google Cloud, focusing on API security. Then came a call from a recruiter.    “Visa was going through the whole transformation around creating open systems, opening up the platform to millions of developers using APIs,” Kumaraswamy recalls. “The hook was, ‘Hey, you can do this at scale.’ You can bring the same mindset, your passion, and all the experience … to one of the largest payment security payment companies in the world.”  He accepted the role in security engineering and security architecture in 2015. A decade later, he is leading cyber strategy as the company’s CISO.   Cyber Leadership at Visa  Related:5 Smart Hardware Moves CIOs Are Making During Tariff Uncertainty More than 1,000 people work in cyber at Visa, according to Kumaraswamy. “I’m really proud of the fact [that] the bench is very strong. We have top talent across multiple locations, not just in the US — across the globe,” he says.   That bench of talent works in six vertical functions within cybersecurity: governance, risk and compliance; access control and management; cyber engineering; cyber defense; cloud security; and security architecture and engineering.   Kumaraswamy works closely with Rajat Taneja, Visa’s president of technology. “I’m very fortunate to have a CTO who thinks cyber first,” says Kumaraswamy. “That sets the tone at the top. Saying that, ‘Hey, we do have to innovate in technology and payments. But if you don’t do cyber, well, nothing matters.’ It’s an existential threat for Visa.”  Avoiding Complacency   Gartner rates Visa’s cybersecurity maturity. “When I started my career path here at Visa in 2015, it was about 3.2 out of 5,” Kumaraswamy shares. “For the last two years, we’ve been given a score of 4.9 out of 5.”  While those numbers are a testament to Visa’s investments in cybersecurity, Kumaraswamy hardly sees them as a given. Cyber threats are constant and ever-changing.   Looking back at his years with Visa, Kumaraswamy recalls working through the aftermath of the Log4J zero-day vulnerability in 2021. He and his team spent four weeks sweeping hundreds of applications using Log4J and potentially open to attack.   Related:How CIO Kristy Folkwein Is Building an IT Team for ADM’s Digital Future “It was around the clock effort and literally hundreds of people, maybe thousands of people, in the company, were involved in the technology to make sure we mitigated this in a very short order,” he says. “I think that also gave us a lot of exposure to how we should think about the next Log4J.”  There will be, inevitably, more zero days and more cyberattacks. “When you wake up in the morning, [the] first thing you think about is, ‘Am I paranoid enough?’ Complacency is the enemy of security,” says Kumaraswamy.   Pushing Cybersecurity Forward  Kumaraswamy is always thinking about talent and technology in cybersecurity. Talent is a perennial concern in the industry, and Visa is looking to grow its own.   The Visa Payments Learning Program, launched in 2023, aims to help close the skills gap in cyber through training and certification. “We are offering this to all of the employees. We’re offering it to our partners, like the banks, our customers,” says Kumaraswamy.   Right now, Visa leverages approximately 115 different technologies in cyber, and Kumaraswamy is constantly evaluating where to go next. “How do I [get to] the 116th, 117th, 181th?” he asks. ”That needs to be added because every layer counts.”  Of course, GenAI is a part of that equation. Thus far, Kumaraswamy and his team are exploring more than 80 different GenAI initiatives within cyber.  “We’ve already taken about three to four of those initiatives … to the entire company. That includes the what we call a ‘shift left’ process within Visa. It is now enabled with agentic AI. It’s reducing the time to find bugs in the code. It is also helping reduce the time to investigate incidents,” he shares.   Visa is also taking its best practices in cybersecurity and sharing them with their customers. “We can think of this as value-added services to the

The chief digital officer (CDO) role has generated significant discussion in recent years, raising questions about its true value and the misunderstandings surrounding it. With the explosion of AI and the expectations it has placed on leaders, the role of the CDO is more relevant now more than ever. This observation highlights the potential for existing roles, such as CIOs, to evolve into CDOs.  The rapid evolution of technology management has expanded the expectations for leadership, meaning traditional CIO roles may no longer suffice in addressing the complexities of today’s macroeconomic environment and the era of AI. Organizational strategies must adapt, and CDOs are essential to drive this transformation.  Are you a CIO or in a similar position and curious about what transitioning to a CDO role would be like? Read on to see if adopting the CDO role would help your organization realize greater value.    Technology Meets Business   How is a CDO different from a CIO? Simply put: CIO role + strategic business vision = CDO. This elevated role not only covers IT operations but also focuses on cybersecurity, risk, and compliance. A CDO is responsible for strategizing how to enable, protect, and transform an organization through technology.  Related:How CIO Kristy Folkwein Is Building an IT Team for ADM’s Digital Future Being both a technology and a business leader, a CDO oversees a broader range of operations beyond just IT infrastructure. They position themselves to drive digital transformation by developing and executing a strategic vision that propels the business forward. When organizations add a CDO to the executive suite, CEOs and boards seek a leader who balances growth, risk, and protection.  In today’s competitive and fast-paced business environment, merely maintaining the IT status quo is insufficient. Organizations require a CDO to see the bigger picture, connect more dots, and make decisions based on the direct impact of IT on business outcomes. Transitioning from CIO to CDO involves moving away from daily operations to concentrate on how technology drives sales, enhances customer engagement, and fosters innovation. Since the CDO’s role encompasses enterprise risk and compliance, they must balance innovative ideas with the challenges of security. There’s also often more engagement with an organization’s board and risk audit committees to address how digital transformation impacts shareholder interests.    Bringing Value  A key way a CDO delivers value is by remaining closely aligned with business needs. By questioning existing processes and tools, a CDO ensures that the organization extracts the maximum value from its technology investments. The question “Is this really moving the needle?” underpins every decision made by a CDO.  Related:The Pros and Cons of Becoming a Government CIO The CDO also adds discipline to operations, ensuring that both existing and new tools are cost-effective, streamlining unprofitable workflows, and leveraging data to discover growth opportunities. A prime example is evaluating AI capabilities within organizational tools. When adopting AI, a CDO critically assesses whether the technology adds value, adheres to security and data privacy standards, and justifies the investment. Gartner predicts that by 2027 enterprise application costs will increase by at least 40% due to GenAI pricing, meaning balancing enablement, costs, and compliance will be increasingly difficult.  Once AI tooling is selected, a CDO collaborates with human resources and internal communications to effectively launch the technology. Unlike the traditional CIO model, which often is siloed, a CDO works early in the process with internal partners to enhance user experience through comprehensive communication, resources, and training — especially regarding the safe use of AI. By embedding controls within the technology framework, a CDO bridges agility and security to optimize the AI experience for both the business and its employees.  Related:Visa CISO Subra Kumaraswamy on Never Allowing Cyber Complacency Key for Success   Having transitioned from CIO to CDO at Dayforce, a leader in HCM technology, I can say with firsthand experience that it can be challenging to widen your mindset to think differently. It can also take time for your colleagues to view you differently and not just think of you as an “IT person.” Getting a bigger seat or voice at the table can be hard, but with the support of internal champions across the organization, I’ve made significant inroads during my transition to CDO.  Here are the top lessons I’ve learned along the way:   Trendspotting with discernment: Staying abreast of the latest technology trends is vital, but a savvy CDO must separate genuine innovations from the noise. Assess new technologies with a critical eye, ensuring that any adoption will help accelerate business priorities and drive tangible benefits to the bottom line.  Mind on the money: Speaking of the bottom line, a successful CDO keeps ROI at the forefront. If your background as a CIO leans heavily on technology knowledge, start amping up your understanding of your organization’s finances. Be a big-picture strategist rather than narrowly focusing on IT.    Aligning on AI: Getting buy-in from leadership on a value-driven, integrated AI strategy is critical — and it all starts with defining measurable goals with input from stakeholders across the organization. CDOs are often responsible for providing strategic counsel on the state of existing infrastructure, how operations will be redesigned, and what IT tools will drive workforce innovation, mitigate risks, and maximize ROI. Once departments are aligned to a shared strategy, the true work begins.   source

Some researchers spend all their professional lives at research facilities because they can spend all their time innovating without being bound by business constraints, such as time to market. According to Krishna Dubba, CTO and co-founder at event sponsorship platform provider CoVent, while both disciplines provide continuous learning opportunities, the intersection of two mindsets can serve businesses and their CIOs well.  Dubba grew into the role of a researcher after earning a series of IT-centric degrees, starting with a bachelor of computer science degree at Jawaharlal Nehru Technological University. Near the end of the program, he took the only AI courses available in 2004.   “At that time, I realized I needed to study AI more because it was so fascinating, and there was only one university offering a master’s degree in AI in India at that time. It was the University of Hyderabad, which is very research oriented,” says Dubba. “I did a lot of research at the end of the course, trying to find computer viruses using AI techniques.”  Next, he went to work for a hedge fund company working on algorithm development before deciding to go back to school at the University of Leeds to pursue a Ph.D. on a grant from The European Research Commission that covered all costs.  Related:How to Hold Efficient Team Meetings “The European Research Commission is a group of countries that work collectively on research. I got the opportunity to go to different countries and work with different universities,” says Dubba. “I was trying to analyze what is happening in videos using computer vision. It’s easy for humans to understand what is going on, but it’s very difficult for a machine.”  His Ph.D. work focused on “cognitive vision” that allows a machine to recognize objects and comprehend what’s happening in a video. One project involved an airplane at an airport. When a flight lands, a lot of activity ensues on the ground, at the gate, on the plane, and more. Using cognitive vision, the airline was able to identify process inefficiencies that could be used to lower costs and improve safety.  However, as a post-doctorate, Dubba chose a more difficult challenge: Robotic vision.  “During my Ph.D. we used fixed cameras to record video, but with a robot, you need ‘egocentric vision’ because the cameras move with the robot. So, as a post-doc, I could see that everything becomes a more complex understanding of what’s going on in a video,” says Dubba.   From Research Facilities to Startups  Many different industries can use cognitive and egocentric vision for their benefit, so Dubba went to work as a principal researcher at Nokia Tech’s Advanced Research Lab.  Related:5 Smart Hardware Moves CIOs Are Making During Tariff Uncertainty “At the time, Nokia had an eight-camera device, called OZO, that looked like the head of a duck and cost around $50,000. Its purpose was to capture 360-degree views. If you wore a headset, you could experience the video in 3D, meaning you could look up, down, or in any direction to explore it,” says Dubba. “It’s called, ‘presence capture,’ and there were a lot of problems with it because you have to stitch the video from eight cameras together.”  Next, he worked for Nokia Bell Labs solving problems in deep learning. Dubba worked in the Social Dynamics group that is charged with quantifying the unquantifiable.   “[Research facilities like Bell Labs] don’t ask, ‘How fast can we build or how much money can we make?’ They want to understand how it will change humanity, so most projects have a 10-year lifespan,” says Dubba. “We were trying to measure things like the emotion or health of a city, which is a very challenging problem, because it is hard to define and hard to measure, so you must use proxies. We used social media feeds as proxies. For example, a map app can tell you the fastest way to get to a destination easily because it is easy to define and measure, but it can’t tell you what your ‘happy path’ would be as it is vague, subjective, and hard to measure.”  Related:How CIO Kristy Folkwein Is Building an IT Team for ADM’s Digital Future Next, he went to work for automation company Blue Prism, first as a senior research scientist and later as a staff research scientist. At the time, the company was building robotics process automation solutions so organizations could automate business processes. When Dubba joined, the company had recently created an AI lab in London. His job was to set the strategy and recruit the researchers.  “It was fascinating — completely different from what I did before. As a researcher, I never had to worry about the business impact or justify the business case, so I learned how to determine the value of a research project from a commercial point of view,” says Dubba. “We also wrote a lot of patents, four of which were granted by the time I left. We also built a product called, ‘Capture,’ so fast, I realized I was working in an entrepreneurial environment. So, I started thinking that I could found a startup doing the same things.”  The first two companies Dubba co-founded were AI-powered life balance app provider Jeevi AI and enterprise-grade GenAI solution provider A2O. Both companies failed for a common reason: A lack of domain expertise.   “Jeevi AI had 25,000 customers, so we were monetizing the product, but we couldn’t make enough to sustain the business. At A2O, we built a chatbot that allowed users to ask questions on unstructured data and documents using LLMs. We also built a product called, ‘Insights’ that used the structured data users fed it so the users could ask data science queries using natural language,” says Dubba. “But we realized that we were not domain experts, we were all technologists.”  So, for CoVent, Dubba decided to co-found the company with a sales and marketing expert who happened to have the expertise it would take to shape a product that could sell. CoVent is an event sponsorship

Global business leaders are urging CIOs to implement generative AI (GenAI) at scale, in hopes that it will enhance organizational productivity and improve operating margins, especially in the face of budget constraints. Yet delivering measurable cost savings in the near term through productivity proves elusive.  The assumption is that incremental productivity gains from GenAI — faster code development, quicker report generation, swifter customer support — will translate smoothly into financial savings. Yet, despite persistent executive enthusiasm, CIOs struggle to realize meaningful bottom-line improvements from productivity-focused initiatives.   CIOs should adopt a GenAI strategy centered on financial efficiency to cut costs, save cash, reduce losses and risk, and boost near-term return on investment (ROI). Six specific tactics are detailed below. CIOs do not need to do all; they should start with the most feasible and impactful tactic for their organization and should acknowledge that this approach may reshape their GenAI strategy.  Pursue Cost Reduction Within IT  There are three tactics CIOs can use to implement a financial efficiency strategy within their own function and directly reduce the IT budget.  Outsourcing haircuts: Outsourcing constitutes over 13% of the average IT budget, presenting CIOs with opportunities to renegotiate contracts using GenAI.   Related:How Companies Are Making Money from AI Projects Although vendors face challenges in realizing productivity savings, competitive pressures drive outsourcers to offer 5%-20% price reductions, often mid-contract. To capitalize on this, CIOs should benchmark current supplier agreements, engage new suppliers for competitive pricing, and renegotiate or switch providers to achieve significant savings.   Reducing third-party variable spend: CIOs often use small, variable contracts with external specialists. CIOs have successfully cut costs by encouraging their staff to use GenAI for tasks typically handled by contractors. The aim is not to achieve productivity gains or complete project in-sourcing, but rather to incrementally reduce the reliance on external contractors. This approach is most effective in areas such as business analysis, PMO, translation, and regulatory document creation. By leveraging GenAI, internal staff can access on-demand expertise, reducing the need for these external engagements and cutting direct costs by eliminating third-party invoices.  Managed services recontracting: Traditional outsourcing providers rely on knowledge asymmetries and high switching costs to maintain price premiums. GenAI disrupts this by compressing the learning curve for new service providers, especially in contact centers, service desks, and application support.   Related:How to Avoid the AI Customer Experience Cliff Large language models help new vendors quickly acquire organizational knowledge, reducing risks and disruptions associated with switching providers. This gives CIOs stronger negotiating leverage, enabling them to seek competitive bids from lower-cost providers who can swiftly become competent. Switching suppliers often entails increased risk; however, leveraging GenAI strategically within the service desk can mitigate this by accelerating the learning curve and enhancing time-to-value. This reduction in risk makes transitioning to a new supplier more viable, and if the supplier offers lower costs, it can lead to significant savings for the CIO.  To effectively manage services recontracting, CIOs should first assess incumbent lock-ins by identifying key managed services contracts where existing providers leverage their institutional knowledge for price advantages. CIOs should invite competitive bids from challenger providers and compare these with incumbent costs, urging incumbents to match or beat the offers. By utilizing GenAI to flatten the learning curve for new vendors, CIOs can enhance their bargaining power and achieve direct reductions in IT service costs.  Related:How Will You Staff Your AI Workforce for the Future? Unlock Enterprise-wide Cost Reductions  There are three tactics CIOs can use to implement a financial efficiency strategy in nontechnology functions to reduce enterprise-wide budgets and save cash.  Working capital reduction: Excess working capital ties up cash that could be used for innovation or debt reduction and is a significant boardroom topic. CIOs can leverage GenAI-based predictive analysis to improve sales and accounts payable forecasts, reducing the need for idle working capital. By identifying patterns and utilizing unstructured data, and most importantly identifying new predictive factors, GenAI enhances forecast accuracy, enabling CFOs to reduce reserves and redirect funds to growth initiatives.  Improved forecasting directly reduces financial overhead. This approach offers immediate cost savings, especially in industries like insurance, aviation, and government, where capital reserves are crucial.  To reduce working capital, organizations should provide GenAI with comprehensive historical finance data to identify patterns and anomalies that enhance forecast accuracy. This enables CFOs to confidently adjust cash buffers, reducing reserves and freeing cash for growth or cost reduction. It’s crucial to track and evaluate the reinvestment of freed cash to assess the strategy’s effectiveness.  Revolving debt expense reduction: Revolving debt bridges cash flow gaps but incurs high interest costs. GenAI-driven cash flow forecasting helps CIOs and CFOs reduce reliance on expensive short-term financing by refining projections for strategic payment timing and reduced credit line usage, lowering interest expenses. Even small interest cost reductions can yield significant cash benefits without operational changes.  By integrating GenAI with enterprise planning systems, organizations can transform it into a strategic asset that frees funds for innovation and reduces operational costs. To implement this tactic, finance teams should map cash flow timing, deploy GenAI for precise forecasting, and track interest savings directly in the income statement.   Stronger contracts and revenue leakage reduction: Revenue leakage is a significant financial drain caused by weak contract terms, poor contract management, or unenforced pricing adjustments.   GenAI-assisted contract analysis provides a scalable solution by quickly identifying weak terms, ambiguous clauses, and invoice undercollection patterns. It can strengthen contracts to increase revenue and reduce losses, as demonstrated by an electronics manufacturer facing revenue loss due to inadequate pricing provisions.   CIOs should work with general counsel and finance teams to input historical contracts and performance data into GenAI, which can propose renegotiations and highlight anomalies. This leads to increased revenue and benefits the bottom line.   Takeaway CIOs should reposition GenAI as a strategic financial tool focused on measurable savings. By focusing GenAI investments on direct financial outcomes, GenAI becomes a powerful instrument for enhancing fiscal management and achieving near-term ROI, especially crucial in increasingly uncertain business environments.  source