Information Week

One way to see a new country is to become a professional truck driver. Werner Enterprises EVP and CIO Daragh Mahon did just that when he immigrated from Ireland to the US. After about nine months, he wanted to find something different and decided to leverage his prior inventory management experience to embark on a new career.  “I went to work for a company called PeachTree Software as an inventory control manager, but literally everything was considered inventory management — unloading trucks, shipping stuff, running returns. Over the first couple of months, I realized that nothing was automated. It was all spreadsheets at the time,” says Mahon. “I started learning how to code, and I started to write some applications, but I got fed up. I thought, ‘This is just pointless. Why should I build this if I can buy it?’ so I negotiated a deal with Manhattan Associates for a shipping and warehouse management system and signed a contract I had no authority to sign.”  While he wasn’t fired for overstepping his role, the CFO, Teri McEvily, reminded him that he’d violated company policy and that the software ‘better work’ or he would be fired for sure. Mahon worked closely with IT and together they helped Manhattan Associates develop one of their first high-volume shipping systems. Over the next couple of years, he continued to help IT in the afternoon or evenings, after working full-time in the warehouse.  Related:Digital Transformation Is a Golden Opportunity for RGP When PeachTree was acquired by Sage Group in 1999, the IT department was doing an SAP implementation. McEvily was tasked with running the SAP implementation for North America and subsequently globally. She asked Mahon to help with the implementation since he was a supply chain expert.  “I volunteered for and moved into the data migration area, because it wasn’t working and nobody had any data migration experience, nor did I. [Nevertheless,] Teri told me to make it work because it was a mess,” says Mahon. “So, I gathered a bunch of SQL and data guys, we sat down and figured it out. Suddenly, we were doing things with SAP data services that Deloitte and SAP probably didn’t know you could do. I started gradually doing all sorts of SAP work. Wherever there was a need, I filled it, such as running security on the platform. The more I got stuck with technical problems, the more I enjoyed it. I love chaos.”  Meanwhile, his job scope expanded to managing the relationship between the business teams and the service desk and infrastructure. In fact, Mahon and the Sage team virtualized the SAP environment, which was an industry first. When they told SAP what they were doing, they expressly told him not to do it on the grounds that it wouldn’t work.   Related:What a CIO Needs to Do Today to Prepare for Quantum Computing “We installed SAP on virtual servers in a data center, and SAP told us not to do it, but we couldn’t figure out why we shouldn’t do it [because] it would save us a ton of money [and] effort. It worked just fine,” says Mahon. “Over the coming years, I started to work with SaaS platforms Salesforce and Zuora, and that’s kind of what brought me to my build versus buy mentality. This was at the beginning of our move to the cloud, which the CIO spearheaded. We were early adopters, and I just felt it was the wave of the future. As we came out of the SAP implementations, I got involved in business analysis and I remember going to Teri one day and saying, ‘You know, I’m kind of pissed off. I’ve become a jack of all trades and a master of none, when others in the organization own a specific piece of the IT world.”  McEvily told Mahon he was looking at it the wrong way. The reason he found himself in this situation was because he was the only guy she and others could trust to fix problems. (In fact, his favorite award of all was the one given after the 10-year SAP implementation. All the approximately 200 people involved in the deployment nominated Mahon for the award, “Who to call when the **it hits the fan.”)  Related:IT Leadership Takes on AGI Mahon spent just over 20 years at Sage Group, rising through the ranks to director of IT and finally senior director, IT & business applications. After that, he held several positions at Vonage, from director of business services to ultimately senior vice president – global and IT business applications before joining Werner as EVP and CIO in 2020.  “As I moved on into director, VP, and senior VP, and CIO roles, I realized that all of that being kicked around the place, going from one area to another, one problem to another and one **it storm to another was actually a good thing,” says Mahon. “It meant I had cybersecurity and infrastructure knowledge. I ran development teams and the service desk. I worked with all the different business units as well: marketing, sales, contact center, accounting, finance, HR, you name it. So, when I sit down and have an IT conversation with anyone, I’ve been there and done [what they do] to a certain extent.”  Important Lessons Learned Along the Way  Planning is considered critical in business to keep an organization moving forward in a predictable way, but Mahon doesn’t believe in the traditional annual and long-term planning in which lots of time is invested in creating the perfect plan which is then executed.   “Never get too engaged in planning. You have a plan, but it’s pretty broad and open-ended. The North Star is very fuzzy, and it never gets to be a pinpoint [because] you need to focus on all the stuff that’s going on around you,” says Mahon. “You should know exactly what you’re going to do in the next two to three months. From three to six months out, you have a really

IT modernization isn’t a foreign concept at RGP. The global professional services firm advises 70% of Fortune 500 companies on how to plan and execute complex digital transformation projects. However, a few years ago, the Dallas, Texas company recognized an uncomfortable truth: Unless it upgraded its own infrastructure, it risked losing credibility and falling behind competitors.  That realization set off a four-year mission to overhaul the company’s IT framework. The goal? Migrate off legacy systems such as Microsoft Dynamics and embrace a cloud-based architecture built for speed, agility, and flexibility. “We needed teams to work faster and better,” declares Keith Golden, chief information officer. “No one wants to hire a consulting firm that can’t modernize itself.”  The initiative, dubbed Project Phoenix, has rewired workflows — and reshaped results. By swapping out legacy systems, code bases, and data framework for a lightning-fast digital infrastructure, RGP is fueling innovation and dialing up its ability to respond to constantly changing business demands. “This was our chance to lead by example,” Golden says. “We had to stick the landing.”  Speed Bumps For decades, medium and large companies have turned to RGP to address complex staffing needs. Yet after the firm expanded into business consulting during the early 2000s, it found itself increasingly constrained by an outdated IT infrastructure. By 2020, things had reached a breaking point. “We had code bases that vendors no longer supported. We had software systems that couldn’t interact and exchange data,” Golden says.  Related:IT Leadership Is More Change Management Than Technical Management The problems didn’t stop there. RGP’s applicant tracking platform wouldn’t integrate with other critical software. This meant that teams sometimes had to use several systems to accomplish basic tasks. On top of that, brittle code triggered disruptions and occasional breakdowns. “We were siloed,” Golden admits. “In some cases, people had little or no visibility into events.”  Keith Golden, RGP Inefficient manual processes were piling up, Golden explains. This made work far more difficult for the more than 2,600 RGP consultants and specialists scattered across 37 countries. “We weren’t operating at the speed required for today’s business environment. It was clear that we had to adopt faster and more efficient workflows and processes,” he says.  In late 2021, the company launched Project Phoenix, a multi-year modernization initiative. Golden stepped in as CIO for RGP a year later. The firm selected Microsoft Azure and an application stack built around Workday Finance and HCM modules to handle money and people; Salesforce to manage customer relationships; Aperture for applicant tracking; and ContractPod AI, a firm specializing in AI-powered contract lifecycle management.  Related:What a CIO Needs to Do Today to Prepare for Quantum Computing Into the Clouds In early 2024, with Deloitte serving as the systems integrator, RGP began to switch on the new systems. “It was far from a lift-and-shift project,” Golden says. Initially, teams had to assess what data the company had, how different groups stored and organized it, and how people used the data to do their work. Analysts also had to determine how to optimize the data for the new systems. “We had to work through complex issues related to cleaning and preparing data,” Golden notes.  Although RGP mostly uses plugged-in vendor APIs to connect applications, it also had to develop its own APIs and code to optimize the workflows. “We had specialized situations where we needed custom code and specific functionality to get data where it was needed at any given moment,” Golden explains.  Executive alignment and a focus on change management were key factors, Golden says. “Fortunately, we had buy-in from our leadership from start to finish. This provided the support we needed to see the project through to the end.” At the same time, the change management team identified technology gaps, fine-tuned processes, and worked with employees to tweak and adapt the new workflows.  Related:IT Leadership Takes on AGI The resulting platform addresses today’s business requirements — yet it’s also engineered for the future. This includes support for specialized artificial intelligence and agentic AI tools embedded in Salesforce and other enterprise applications. Fueled by agile teams and continuous improvements, RGP has developed a global playbook that keeps the business at the leading edge of innovation.  Agility on Demand The project wasn’t without challenges. For example, one small vendor was supposed to build out additional functionality within RGP’s time tracking application, which consultants in the field use for billing. Internal teams had already begun writing code and developing APIs — based on a planned acquisition by Workday. However, six months before the system was supposed to go live, a different company acquired the software firm. “We had to go back and revamp all the code,” Golden says.  Yet, overall, the modernization initiative progressed smoothly, Golden says. Today, teams are working faster and more efficiently across numerous areas. For example, when RGP receives a request from a client to find qualified candidates, job openings flow from Salesforce into Aperture. It can then match qualified candidates and rank them based on specific criteria, including skills and role requirements. “This eliminates the need for recruiters to dig through piles of résumés,” he says.  Recently, when an oil and gas client needed to fill 90 finance roles as part of its own transformation project, RGP’s team delivered ranked matches within hours — a process that in the past required days or even weeks. “While we didn’t succeed with every placement, we captured more than our share of business by identifying high-quality candidates quickly,” Golden says.  Contract management is also simpler. In the past, if a client wanted to use its own templates for the review process, a document would often sit in email inboxes for hours or days until an attorney could review it. If someone happened to be on vacation, the entire process stalled out. Making matters worse, “Tracking changes was messy and inefficient,” Golden says. Now, the role-based contract management system routes the contract to the first qualified and available attorney.  RGP is now eyeing other improvements, such as

An emerging avenue of AI, applied affective computing (AAC), holds immense potential despite being in its early stages. AAC enhances human-computer interaction by integrating AI, robotics, and engineering with social science, psychology, and medical science.    In the generic human parlance, AAC is a reflection of what we call empathy. As technology becomes universally accessible through cloud, open-source, AI, and low-code platforms, the race to outperform is no longer just about features; it’s about human connection.   And for CXOs leading high-tech firms, integrating empathy into strategy isn’t a soft initiative; it’s a powerful business lever with measurable impact. Empathy is today regarded as big business, and the global affective computing market is expected to reach USD 338.28 billion by 2030.  The Shift from Capability to Connection  This shift was bound to happen. In today’s rapidly changing competitive scenario, the historic differentiators of technological prowess — speed, computing power, and functionality — have become default attributes. Both the game and the playing field have been drastically disrupted. Empathy, the ability to deeply understand and respond to the needs, feelings, and challenges of users and stakeholders, is emerging as a powerful differentiator in the hi-tech industry.   Related:IT Leadership Is More Change Management Than Technical Management Thus, technology is no longer just about systems. It’s equally about people — their experiences, expectations, context, and diversity of thoughts and reactions. With AI’s ultimate goal of making human-like machines, empathy stands as the definite bridge between engineering and human experience. For example, Microsoft has an inclusive design philosophy that ensures its products serve people with disabilities while enhancing usability for everyone. Salesforce recognizes the impact of algorithms on human lives and integrates empathy into its technology governance. Even startups recognize this important need: Headspace and BetterHelp leverage technology to scale mental health support, an inherently empathetic service, to millions.  And here is an undeniable truth, and it is not about whether technology can replace human skills. Be it AI or automation, they need the human touch to evolve. Their ascent to such incredible heights has been made possible by human ingenuity, and this will not change.  Why Empathy Matters Now More Than Ever   Neuroscientific research has firmly established that emotions are an integral component of learning, perception, and decision-making. When applied to evolving consumer expectations, this has significant implications. Today’s users do not just want products that work; they demand products that understand them. They expect frictionless experiences, personalized journeys, inclusive design, and brands that reflect their values. This is true across industries, whether it’s a fintech app in rural India or an AI assistant for a Fortune 500 CEO.  Related:Digital Transformation Is a Golden Opportunity for RGP It is therefore no surprise that AI and automation seek the human touch. Especially since there is an increasing risk of alienation or bias, AI becomes embedded in products and workflows. Empathetic design thus becomes a vital aspect of technology development. It not only mitigates the risk of bias but also proactively ensures that AI respects the need for fairness through ethical design, transparent algorithms, and human-in-the-loop systems that listen, adapt, and learn responsibly.  In a crowded digital market, customer retention hinges on relationships that enjoy an emotional connection. Brands that demonstrate empathy through responsive support, accessibility features, and thoughtful engagement strategies earn customer loyalty and advocacy that outlast price wars and product comparisons.   Empathy extends beyond external stakeholders of an organization to its internal talent force. Here too, retention depends on relationship, and an empathetic approach fosters psychological safety for employees to stay and engage with motivation and happiness, both powerful drivers of innovation. An interesting case is that of Acer’s approach to hybrid work, which provides flexible schedules around individual productivity rhythms and trains managers to focus on engagement, rather than monitoring.  Related:What a CIO Needs to Do Today to Prepare for Quantum Computing Embedding Empathy into the Tech DNA  For empathy to be a sustainable differentiator, it must be embedded in the culture, processes, and products of hi-tech organizations. Imagine an enterprise-wide culture where human-centered design leads product development cycles, where ethnographic research informs and guides business strategy, and where cross-functional teams enjoy diverse voices at the decision table. This is true empathy in action, and it calls for leadership that promotes diverse teams, open communication, collaborative problem-solving, and an engaging workplace culture, all of which are essential to thrive in today’s complex and fast-paced tech landscape.  In an increasingly data-led business environment, analytics can be a great means to achieve this outcome. The hidden value of data lies in the human story that creates every data point. When empathy is woven into data analysis, deeper insights can be unlocked, leading to greater ethics and integrity in decision-making.  The ROI of such an approach is as huge as it is measurable. A recent report estimates that fostering empathy in the workplace could lead to an estimated USD 180 billion in employee attrition savings.    So, in leading the next era of high-tech, let’s build with heart, measure with rigor, and embed empathy in every code, conversation, and corner of our organizations.  source

Artificial general intelligence (AGI) is already being hyped but realizing it will take time. How much time is highly debatable. For example, Sam Altman stated he thought AGI would be achieved by 2025, which was earlier than other estimates. Later Altman changed the forecast to “during Trump’s term.” Most recently, he’s said that AGI is a pointless term and some IT leaders agree, arguing that AI is a continuum, and that AGI will be realized incrementally rather than suddenly.  “[W]e think about AGI in terms of stepwise progress toward machines that can go beyond visual perception and question answering to goal-based decision-making,” says Brian Weiss, chief technology officer at hyperautomation and enterprise AI infrastructure provider Hyperscience, in an email interview. “The real shift comes when systems don’t just read, classify and summarize human-generated document content, but when we entrust them with the ultimate business decisions.”   On the 2025 Gartner Hype Cycle for AI graph, AGI appears behind but relatively close to other forms of artificial intelligence, including AI agents, multimodal AI and AI TRiSM (ethical and secure AI), which Gartner recommends IT leaders focus on in 2025.   OpenAI’s newly released GPT-5 isn’t AGI, though it can purportedly deliver more useful responses across different domains. Tal Lev-Ami, CTO and co-founder of media optimization and visual experience platform provider Cloudinary, says “reliable” is the operative word when it comes to AGI.  Related:Unum Group CIO on How to Prioritize Learning and Relationships “I predict we will see functionally broad AI systems that appear AGI-like in limited contexts within the next five to seven years, especially in areas like creative content, code generation and customer interaction,” says Lev-Ami in an email interview. “However, true AGI [that is] adaptable, explainable and ethical across domains is still likely more than 10 years out.”  Tal Lev-Ami, Cloudinary Other estimates are even longer. For example, Josh Bosquez, chief technology officer at public benefit software provider Second Front Systems, thinks AGI probably won’t be a reality for one or two decades, and that reliable, production-ready AGI will likely take even longer.  “We may see impressive demonstrations sooner, but building systems that people can depend on for critical decisions requires extensive testing, safety measures, and regulatory frameworks that don’t exist yet,” says Bosquez in an email interview.   Jim Rowan, principal, Deloitte Consulting and US Head of AI, says that while the timeline for and definition of achieving AGI remain uncertain, organizations are already preparing for its arrival.   Related:How CIOs Can Work With CFOs on Sufficient Project Funding “By implementing standards, addressing regulatory challenges and optimizing their data ecosystems, companies are strengthening current AI capabilities and laying the foundation for AGI. These proactive measures make the path toward AGI feel increasingly within reach,” says Rowan in an email interview.   Any estimates of AGI’s arrival are subject to change, given the accelerating rate of AI innovation and emerging regulation.  Challenges With AGI Artificial narrow intelligence or ANI (what we’ve been using) still isn’t perfect. Data is often to blame, which is why there’s a huge push toward AI-ready data. Yet, despite the plethora of tools available to manage data and data quality, some enterprises are still struggling. Without AI-ready data, enterprises invite reliability issues with any form of AI.  “Today’s systems can hallucinate or take rogue actions, and we’ve all seen the examples. But AGI will run longer, touch more systems, and make higher-stakes decisions. The risk isn’t just a bad response. It’s cascading failure across infrastructure,” says Kit Colbert, platform CTO at Invisible Technology, a software services provider supporting the AI value chain, in an email interview. “We will need a sophisticated set of safeguards in place to ensure this doesn’t happen. Today these exist as basic access controls to sensitive systems, but with AGI we’ll need much more advanced mechanisms.”  Related:Beyond Borders, Beyond Bandwidth: A CIO/CISO’s High-Seas Mission Deloitte’s Rowan says his company’s concerns are less about the technology and more about organizational preparedness and potential mismanagement.   “Without the right frameworks and governance, AGI implementation could amplify existing challenges, such as strategic misalignment. Robust preparedness will be crucial to maximize AGI’s benefits and minimize its risks,” says Rowan. “As with previous AI advancements, CIOs should approach AGI with a strategic and business focused approach that looks for opportunities to drive long-term value. [S]tart with low-risk, high-value pilots that improve internal productivity or automate repetitive tasks before expanding AGI to solve cross-departmental challenges. This phased approach helps teams adapt gradually, builds trust in AGI systems and allows operational challenges early.”  Jim Rowan, Deloitte Cloudinary’s Lev-Ami is concerned about hallucinations and opacity.  “My top concern is [the] ‘illusion of understanding.’ Systems that sound competent but have no grounded comprehension can cause real harm, especially when used in high-stakes decisions, accessibility or misinformation-heavy contexts,” says Lev-Ami. “I’m also concerned about opaque dependency chains. If core business logic starts relying on evolving black-box models, how do we ensure continuity, accountability and auditability? Even if we carefully test the AI, once we give it full autonomy, how can we trust what it will do when it encounters a situation it’s never seen before? The risk is that [AGI’s] mistakes could be unpredictable and potentially unlimited.”  David Guarrera, EY Americas generative AI leader believes today’s challenges will remain challenges for AGI. “Power and resources are becoming increasingly concentrated in a small number of technology companies, creating a new form of digital hegemony that could have broad societal implications,” says Guarrera in an email interview. “At the same time, we’re witnessing the spread of misinformation and a flood of low-quality AI-generated content [that] threatens to degrade the information ecosystem people rely on to make decisions. These trends risk fueling greater polarization, as algorithms reinforce divides and push communities further apart.”  There are also economic concerns. “[A]utomation is already displacing certain categories of jobs, and AGI would likely accelerate that trend dramatically. Beyond job loss, we face the possibility that agentic workflows could make catastrophic mistakes or hallucinate in ways that cause real-world harm if given too much autonomy,” says EY’s Guarrera. “Looking further ahead, AGI raises the

Launching an important new venture requires various resources, not the least of which is money. That’s why it’s important for a CIO to work closely with the enterprise’s CFO to ensure that adequate funds will be available to achieve success, even if initial cost estimates prove to be overly optimistic.  Technology has never been more important for business than it is today, and CFOs are finely attuned to the challenge, says Matthew Guarini, executive director of the Technology Business Management Council, a community of business technology leaders dedicated to advancing technology business management. “CFOs now prioritize technology over areas such as talent and supply chain, which demonstrates a significant shift in strategic investment focus toward technology for boosting growth and revenue,” he observes.  Working closely with the CFO allows the CIO to shift the perception of IT from a cost center to a strategic enabler, says Beth Weeks, executive vice president of development at project planning technology and services provider Planview. “CIOs need to be able to provide real-time visibility into delivery friction, bottlenecks, and flow metrics so they can present a clear, financial narrative that helps CFOs see what’s working and what needs reevaluation,” she explains.  Related:Unum Group CIO on How to Prioritize Learning and Relationships A Mutual Partnership CIOs can build closer partnerships with CFOs simply by providing full transparency into how tech investments create value for the business rather than just the IT department, Guarini says. CIOs also need to demystify tech spend by showcasing the value their investments deliver to the business in terms of revenue, productivity, innovation, risk reduction, experience, and sustainability. “With a clearer understanding of tech’s value and its drivers, CIOs can help their CFO counterparts create better strategies that deliver shareholder value while enabling more accurate budgets and forecasts for optimizing internal delivery.”  A CIO should work side by side with the CFO, particularly in terms of project funding, advises Uku Sööt, organizational growth strategist at communication and collaboration services IPB Partners. “It’s not only understanding tech, it’s also knowing more about the wider financial world,” he says. “Once CIOs and CFOs are on the same page, funding decisions can be based on a professional grasp of both the return on investment and financial priorities.”  Building an Alliance To establish a strong relationship with the CFO, the CIO must avoid the prevailing attitude of IT versus finance while adopting a business-first approach, Sööt says. The first step should be learning the CFO’s priorities — cost control, risk management, and profitability — and then discussing technology decisions around those issues, he recommends.  Related:Beyond Borders, Beyond Bandwidth: A CIO/CISO’s High-Seas Mission Sööt recalls he’s personally achieved success by demonstrating to CFOs how IT projects can have a positive impact to revenue generation and/or cost-saving. “As an example, in a conversation on cloud migration project, I demonstrated how it can scale operations without spending more on infrastructure,” he says. “I always focus on establishing trust through alignment of technology and business objectives.”  Achieving a Balance The biggest mistake CIOs make when working with a CFO is failing to understand what’s important to the business and the CFO, Guarini says. This can result in misalignment when the CIO is delivering on their plan, yet the strategy isn’t helping the CFO deliver on their goals.  Still, despite a CIO’s best efforts, it’s often not easy to handle a CFO who’s primarily interested in saving costs, Sööt observes. He recommends focusing the discussion on value rather than expenses. “I’ve encountered cases where the CFO was obsessed with the immediate cost of a certain project, yet I altered the course of the discussion by demonstrating the advantages of the long-term results,” Sööt says. “For example, with a client interested in using an AI-based customer support system, I focused on the lower long-term cost of customer service and the possibility of serving more customers without increasing the number of employees.”  Related:Why Cloud Efficiency is Driving More IT Spending (Not Less) Final Thoughts The most productive CIO-CFO partnerships prioritize transparency and shared accountability, Weeks says. “When these two functions are working in lockstep, more strategic, confident investment decisions can be delivered across the enterprise.”  Building a strong partnership between the CFO and CIO is the ticket to technology success, Guarini says. “With the right data and insights from the CIO, CFOs can make more informed decisions about technology investments.”  People will never agree on everything, but the most important thing is to keep a conversation going, Sööt advises. “I always ensure that I keep in regular contact with the CFO, not only when there is a discussion of funding, but all along the project lifecycle,” he says. “Constant communication creates a long-term trust, and both parties will always be oriented toward a single final goal.”  source

Unum Group EVP Chief Information and Digital Officer and former Aflac EVP and CIO Shelia Anderson kicked off a high-tech career back in the late 80’s when few women could even hope to attain IT leadership positions. She earned a B.S. in computer science at Louisiana Tech University and an M.S. in engineering management at Southern Methodist University before starting her career in a tech world still dominated by mainframes, while the market for clunky PCs was expanding. Not long after, “local area networks” or LANs emerged, and the “killer app” was printing, followed by the interconnection of PCs or networking as we know it today.  Anderson’s first job was working for global tech consultancy Electronic Data Systems (EDS) as a technology consultant.  “[At the time,] we didn’t have all the big technology consulting firms that we have today. I went through EDS’s systems engineering development program, which was an industry-leading ‘tech boot camp’ at the time,” says Anderson. “[It was] a very disciplined approach to learning how to code and how to do technology the right way. You learned a lot of basic skills, [some of which I use] in my disciplined approach today.”  A few years later, the internet appeared as The Next Big Thing because it was obvious ubiquitous global interconnection would change everything. By this time, Anderson was already doing Internet consulting for a group within EDS that was spun off as a startup called “Chaos to Order.” Its charter was to develop innovative solutions using all internet-related emerging technologies.  Related:How CIOs Can Work With CFOs on Sufficient Project Funding “The internet was my first love. I developed new skills and learned many new and emerging internet technologies,” says Anderson.  Kicking Her Career into High Gear Keeping current on technology has always been important for a tech leader, though the job is no longer all about tech. There’s also an important human factor that Anderson learned to appreciate early on that included navigating gender bias.  “Today, we have a lot of inside and outside support, but at the time you had to learn how to navigate those perspectives and perceptions on your own,” says Anderson. “It taught me the importance of showing up strong and making the most of your seat at the table. You had to be prepared to contribute to those discussions meaningfully, ask thoughtful questions, and help drive the conversation forward. That’s how you demonstrate your value — by adding insight and making an impact that others can clearly see.”  Meanwhile, she was about to experience a common obstacle, which is balancing a demanding job with parenthood, which was more difficult then than it is now, given modern HR practices. Anderson found balancing work and home so difficult, she questioned what she “should” be doing.  Related:Beyond Borders, Beyond Bandwidth: A CIO/CISO’s High-Seas Mission “I was leading a very demanding transformation around a large system development initiative [with] never-ending working days and nights. And those were the days when you did not have the ability to work from home, because we had a green screen,” says Anderson. “If you had an issue, you could log in and see it, but to do the work, you had to drive into the office. I reached a point where I felt I was just not doing my best at home or at work when I returned into this pressure cooker of an environment. I quickly got to the point where I said, ‘Okay, this isn’t working. I’m going to have to quit,’ because I’m not doing a great job and I’m letting everyone down on both sides. [Surprisingly,] a male advocate who was very supportive asked what I needed.”  She kept her job, albeit at 40 hours, and was able to continue building her career.  “When I think back, and [wonder] if that [situation] had been handled differently at that time, would I even be where I am today? I don’t know,” says Anderson. “It’s important to surround yourself with people who are going to be both supporters and challengers who help guide you along the path. I’ve had the privilege of working with and for some amazing leaders, teams and companies, and I take that with me everywhere I go.”  Related:Why Cloud Efficiency is Driving More IT Spending (Not Less) After EDS, she was promoted from IT director, business management to director, asset engineering at Hewlett Packard Enterprise. After that, she served as managing director, business advisory services at IT consultancy Grant Thorton. Next, she moved into her first CIO role as vice president and CIO property and casualty at financial services firm USAA, then to EVP and chief information officer at Liberty Mutual Insurance. Most recently, she was EVP and CIO at insurance company Aflac.  Strong, Positive Relationships Are Critical Anderson places great importance on building and maintaining strong relationships. In fact, she’s hired prior technology leaders with whom she worked at previous jobs to help lead transformations.  “The CIO role changes every day now. Previously, you had tried-and-true practices you could anchor on, knowing that you could be successful with them,” says Anderson. “Now expectations are far greater. There are always pressures around the expected business value you must achieve in the business relative to all the technology advancements. How do you leverage these new and emerging technologies to drive value through innovation?”  Like other CIOs, she hasn’t had the luxury of keeping the business running at the cost of innovation or vice versa.  “It’s a very intentional focus for me, making sure that I’m carving off both the investment and the time to focus on the value-added capabilities. Today, there’s more emphasis on shortening time to value and measuring that,” says Anderson. “This is truly problem-solving every day, and all of us really [need to] reimagine how we’ve traditionally solved problems. How do I tell that story as a CIO in an organization?”  Recently, she says, there’s a broadening of the CIO role to include adjacent titles. Anderson is one example as

Amit Basu walked into a bank to become a pioneering software developer, only to set sail years later for the greater freedom offered by the maritime industry. “Ironically, it wasn’t the domain but the technology that drew me in. While banks were still running older systems, this company was deploying the latest in database platforms. That technical edge attracted me and, as it turns out, anchored me,” says Basu who is now CIO and CISO at International Seaways, which owns and operates a large fleet of seagoing vessels to transport crude oil and refined petroleum products worldwide.   But Basu hasn’t spent his career chasing the latest new shiny thing in tech. The lure that catches his attention is the opportunity to solve increasingly more difficult business problems. He enjoys puzzling out a solution that is usually part tech but rarely just tech.  Grabbing Opportunity With Both Hands Basu joined a large commercial bank in India in the late 1980s as a software developer right at the onset of banking computerization in the country. He was part of a pioneering team that designed and implemented core banking applications for branch operations.  “It was my first encounter with the direct impact of technology, writing programs that real users depended on to serve real customers. Watching my code in action, powering everyday banking transactions, instilled in me a belief that has guided me ever since: I don’t want to be just a technologist; I want to be a solution provider enabling business to excel. And for that, I need to understand what the business needs, in their language,” he says.  Related:Unum Group CIO on How to Prioritize Learning and Relationships If there’s one industry where one can learn the universal language of business, it is banking and finance. And Basu learned it well. In banking IT, through the mid-1990s, before stepping into the intriguing challenges presented to him in an organization that built software for international banks. While there, he worked on real-time, network-based banking systems designed using relational databases.   Amit Basu, International Seaways “The early challenges of optimizing system performance on constrained hardware, and ensuring data security and integrity, pushed me into learning the intricacies of relational databases. I learned database administration skills, experimenting with configuration and performance tuning inside out, and that expertise became my launchpad into the bigger world,” he says.  From there, he segued to an American bank as a database administrator and moved to the US in 1994. A year later, he made another move: this time to another industry rather than another country. He kept the position of database administrator, but this time as a contractor.  Related:How CIOs Can Work With CFOs on Sufficient Project Funding “Maritime, in those days, was a greenfield for IT, and I took the opportunity with both hands. One of my early successes was implementing the first computers and LAN onboard ships, connecting to shore over satellite and developing data replication systems that crew onboard used to enter data,” Basu explains.   Moving Up and Onward Basu has spent the last three decades in Maritime IT. He transitioned from contractor to a full-time role in 1998 and over time progressed into leadership roles, first as deputy head of IT, then CIO, and today, CIO and CISO at International Seaways.   Over the years, he engineered multiple digital transformations, starting with ERP, then data warehouse and business analytics, cloud computing and SaaS, creating multi-layered cybersecurity frameworks, and now, the AI revolution.   His secret to always moving up in his career? “I’ve always remained focused on creating value for the business and delivered technology that helps the business achieve its goals and gain competitive advantage,” he says.  Yes, we can all agree that is a smart way to progress in IT. But what did that look like from Basu’s point of view? It’s a long and eventful story, he says, but it begins and ends with a mentor who can help you build a strong foundation.  Related:Why Cloud Efficiency is Driving More IT Spending (Not Less) “I entered the world of IT as a rookie developer, knowing only the syntax of some computer languages but nothing about software development. The person who transformed that beginner into someone capable of designing complex business systems was my senior at the bank, Mr. Narayana Bhat. He taught me the ABCDs of application design and development with clarity and purpose. Whatever I’ve built over the years rests on the foundation he gave me, and for that, I remain deeply grateful,” Basu explains.  Career Highlights Several milestones stick out in Basu’s mind as well. The first was one of many filed under the requirement to “just make it work!” Most of the time, that’s much easier said than done.   In one early example, he led a team that successfully deployed an online network-based retail banking solution for a bank in Indonesia. “The entire system ran on hardware with just 32 MB of memory and limited CPU, but we made it work because we believed that with smart design and efficient databases, even the toughest constraints could be overcome,” he says.  He points to another proud moment in 2013 when he championed one of the earliest cloud adoption strategies for the sector. You may recall that in those early days, many scoffed at the notion of cloud computing. But his willingness to step up and embrace it paid off later in an unexpected scenario.   “That decision proved invaluable. In 2020, during the global health pandemic, our CEO, Ms. Lois Zabrocky, publicly acknowledged on national television that the company’s ability to remain 100% productive from day one was made possible by the foresight to move to the cloud years earlier. That was a deeply gratifying moment, both personally and professionally,” he says.  In recent years, he has focused extensively on building a multi-layered cybersecurity framework to protect the company from increasingly sophisticated adversaries. He takes pride in what has been accomplished so far to secure the

Cloud bills that consistently exceed budget forecasts have become the new normal for enterprise technology leaders. Despite aggressive cost optimization efforts, 83% of organizations are spending more on cloud services than anticipated — with the average overspend reaching a staggering 30%. This persistent pattern isn’t a failure of management or forecasting. It’s a manifestation of a 160-year-old economic principle that perfectly explains our modern cloud challenge.  When Efficiency Accelerates Consumption: Jevons Paradox Reborn  In 1865, British economist William Stanley Jevons observed something counterintuitive during the Industrial Revolution. As coal-powered steam engines became more efficient, the total consumption of coal dramatically increased rather than decreased. This became known as “Jevons Paradox“: when technological progress increases the efficiency of resource use, we end up consuming more of that resource, not less as intuition might suggest.  Today, we’re witnessing this same paradox playing out in enterprise cloud computing, but with even greater intensity.  The Evidence: What 300 CIOs Revealed About Cloud Economics  In our recent survey of 300 enterprise CIOs, we uncovered compelling evidence of Jevons Paradox in action. While 80% of organizations report cost savings from their cloud deployments compared to traditional on-premises alternatives, 4% have been exceeding their cloud budgets significantly. Only 2% of organizations came in under budget.  Related:Bentley Systems CIO Talks Leadership Strategy and AI Adoption This contradiction isn’t just theoretical. One financial services CIO explained how they reduced per-transaction costs by 42% through cloud migration, yet their total cloud spend has doubled over three years as they process significantly more transactions and launch services in the cloud that weren’t possible before.  Why Cloud Amplifies the Paradox: Two Accelerating Forces  Two powerful forces in modern cloud environments accelerate this paradox beyond anything Jevons could have imagined:  1. Cost efficiency transformation: Cloud resources continue to become more affordable on a per-unit basis. What may have once required millions for a company to invest in capital investment for on-premise hardware that depreciated over five years now converts to flexible operational expenses that can scale with business needs. The costs for infrastructure in the cloud continues to decline — in 451 Research’s Cloud Price Quarterly, Q1 2025, the firm’s Cloud Price Index found that between Q4 2024 and Q1 2025,  on demand list prices dropped sharply for several infrastructure resources, consistent with long-term trends, e.g., database storage decreased nearly 25% quarter over quarter and NoSQL databases decreased 40% quarter over quarter. This general deflationary trend reflects the continuing race to drive cost-per-unit down.  Related:Policy Matters: Navigating the Brave New World of Immigration 2. Consumption agility: Unlike the original Jevons scenario that focused solely on cost efficiency, cloud computing introduces unprecedented deployment speed. When a new market opportunity emerged in pre-cloud environments, IT teams spent months procuring and configuring hardware. Today, development teams deploy new capabilities in minutes.  As a retail CIO told me, “Before cloud, launching a new customer analytics platform took six months and a seven-figure budget. Now my teams can experiment with new services for thousands of dollars per month and scale only what works. We’re getting significantly more value but spending more overall.”  From Cost Control to Value Creation: The Leadership Challenge  As a technology executive, I see this paradox playing out across our industry. Business and IT leaders regularly launch new cloud-based services and play “whack-a-mole” with unexpected cost spikes as innovation accelerates. The difference between organizations that struggle with cloud economics and those that thrive isn’t about spending less — it’s about generating more business value from each dollar spent.  Related:Empathy: The Strategic Differentiator for CXOs in Tech This explains why 56% of CIOs report that their CEOs and boards support current spending levels and would approve further increases, while 43% acknowledge concerns about cloud costs. The executives who understand the paradox recognize that optimizing simply for the lowest spend often means sacrificing innovation and competitive advantage.  Strategic Approaches: Beyond Basic Cost Optimization  While Jevons Paradox explains the pattern we’re seeing, it doesn’t mean organizations should simply accept uncontrolled cloud spending. The most successful enterprises are implementing sophisticated approaches that balance optimization with innovation; including:  1. Implementing business-aligned FinOps: Move beyond technical metrics to business outcomes. One healthcare technology company we work with doesn’t just track cloud cost per instance — they measure cost per patient served and revenue generated per cloud dollar spent.  2. Optimizing application efficiency: Look beyond infrastructure. Most enterprises only focus on right-sizing instances or reserved capacity purchases, missing additional opportunities. At Azul, we’ve seen organizations further reduce cloud compute resource consumption by 50% by optimizing their application runtime environments, particularly for Java workloads that power most enterprise applications.  3. Creating developer economic awareness: Many organizations discover that developers are unintentionally creating costly architectures. One financial services company implemented a “bill of materials” approach where teams forecast the cloud resources needed before deployment, creating accountability without restricting innovation.  4. Embracing continuous optimization: Cloud economics isn’t a one-time effort. One retail client implemented automated monitoring that alerts when spending patterns deviate from expected business metrics, allowing them to quickly identify both wasteful spending and unexpected business opportunities.  The Future of Cloud Economics: What CEOs and Boards Need to Understand  As AI workloads grow exponentially and enterprise cloud adoption similarly accelerates, expect Jevons Paradox to come into play even more intensely. Organizations deploying generative AI solutions today report computing requirements growing at rates that eclipse any previous technology wave. The CIOs who will succeed in this environment aren’t those focused narrowly on cost reduction but those who maximize business value from cloud investments.  The enterprises that thrive will shift from treating cloud as a technology expense to viewing it as a business accelerator with measurable ROI. Board-level discussions must evolve from “How can we reduce cloud spending?” to “How can we maximize the business value generated from each cloud dollar?”  After all, in today’s ever-changing technology world, the goal isn’t to use less cloud — it’s to create more value from it.  source

Dashboards are expensive. Beyond the investment in a particular platform, companies sink thousands into the time it takes for specialists to build the dashboard. The hundreds of staff hours spent in meetings about the metrics. That’s not cheap. Add in the opportunity cost of delayed decisions while waiting for the perfect dashboard to be built.   For all that investment, you’d expect a pretty good return. So, then why is it that so many BI dashboards gather dust?   You know your dashboard is working well when you see usage metrics in acceptable ranges and frequencies. It’s doing its job when you see decision makers reference dashboard data in meetings. And, you know the dashboard is engaging when you get requests for updates, adjustments and additions.   However, most of the time? You get crickets from the business side. Silence!   I’ve consulted hundreds of companies about their data visualization, resolving pain points and introducing solutions, and “dashboard underwhelm” is one of the most common issues that pops up, regardless of industry. In those conversations, I’ve seen patterns that predict a dashboard’s lifespan. Watch for what follows.  Trying to Make too Many People Happy  The developers tasked with dashboard construction likely consulted with multiple departments, and roles within those departments, to get input on what the dashboard should report. The problem is that everyone needs different information to do their jobs well.   Related:Why Master Data Management Is Even More Important Now The developers — who naturally want to please their supervisors — then make a dashboard where they’ve tried to cram in everyone’s hopes and dreams. These dashboards invariably become both visually overwhelming and actionably underwhelming because any given viewer has to dig through irrelevant visuals to get to what matters to them. People will dig only so far before they give up.  To do dashboarding right, you need different metrics in different layouts for different audiences. CEOs don’t want to widget and drop-down their way to the bottom line. They want interpretation of the key indicators that matter the most to them.  Managers, on the other hand, likely need those drill-down menus so they can investigate issues. A dashboard suitable for management will inherently be more complex.    Requiring Too Much Insider Knowledge  The best clue that a dashboard is likely to die a quick death: a set of unrelated numbers in a large font up at the top. Depending on your industry, you might refer to these as your key performance indicators KPIs) or big ass numbers (BANS). Whatever you call them, they lose your audience fast.  Related:InformationWeek Podcast: Proving Tech Investment’s Company-wide Value Let’s use an example. Monthly Active Users: 4,283,912  The only people who can make sense of that number are the people who are so close to the data for monthly active users that they can look at 4,283,912 and tell you whether that’s good, bad, or same as yesterday. Interpreting that number takes a lot of insider knowledge. It’s only a helpful way of reporting for your power users.   Everyone else needs context so they can make meaning out of that number. They’ll need to see the history of monthly active users to determine how it’s trending. They’ll need to see how that number relates to the annual goal.   Without that context, the number is just decoration. It’s something to glance at, not something to act on. And when your dashboard doesn’t lead to action, it stops getting used.  A Dashboard Is the Wrong Container for the Data Dashboards came of age before our lives revolved around screens. They were initially meant for C-suite executives to get the high-level view of their KPIs while marching from one meeting to the next.   We don’t operate like that anymore, but we’ve still clung to the notion that dashboards should entirely fit within one screen. This design parameter leads to cramped displays that people don’t want to use.  Related:Experian’s Lintner Discusses AI Transformation at the Credit Bureau Yet at the same time, the demand “We need a dashboard!” has become popular — so much so that we task developers with creating these because it sounds sexy even if it isn’t actually the right container for the data.   Perhaps some of your audiences would benefit more from a static one-page handout with contextual narrative so the reader better understands the information displayed. Maybe the right container looks more like a website where there’s a mix of images and explanations that can convey the meaningful interpretation of the data. People scroll these days. It’s ok if the information spans beyond one screenshot — so long as that information is informative and useful.   Dashboards don’t automatically improve decision-making just because they look slick or use the latest BI platform. If they’re visually intense, overly generic, or hard to interpret, they will be ignored, no matter how much they cost.   But when dashboards are thoughtfully designed, aligned with audience needs, and built for real-world use instead of trendiness, they become a powerful tool. So, before you launch another dashboard project, ask: Who is this really for? What decisions will it support? And, is a dashboard even the right solution? The answers to those questions will save your organization a lot of time and money.  source

The United States has long been the world’s go-to destination for business and technology innovation. From Silicon Valley to Boston’s biotech hub, American companies have lured exceptional talent from every corner of the globe. However, that draw is now fading. New barriers for work visas and green cards are prompting top talent to weigh opportunities elsewhere.  This potential brain drain won’t arrive in a flood. It’s more likely to occur as a slow drip that extends over years. Authorities may continue to block renewals for some IT workers on H-1B, O-1, EB-1A, or National Interest Waivers through onerous restrictions, high fees, and aggressive rhetoric. Meanwhile, future talent — typically international students on F-1 visas — may accept jobs or launch startups elsewhere.  One thing is clear: CIOs, caught in the crosshairs, must adapt. Without top-tier IT talent, “We may never see some of the breakthroughs that these people would have brought to the US,” says Jeff Le, managing principal at consultancy 100 Mile Strategies and a visiting fellow at the National Security Institute at George Mason University.  The takeaway? CIOs cannot treat immigration casually. It must become part of a broader business playbook. This means rethinking and reworking internal policies, experimenting with new tools and technologies, and finding ways to keep pace with abrupt changes in policy.  Related:Why Cloud Efficiency is Driving More IT Spending (Not Less) Beyond Skills Immigration critics as varied as Bernie Sanders and Steve Bannon view H1-B visas merely as a cost-cutting tactic or a way to undercut domestic wages. What’s often overlooked is that companies hiring foreign workers face increased compliance costs, legal fees, and administrative overhead. In addition, employers must file a Labor Condition Application affirming that an employee will not lower wages or negatively impact working conditions for equivalent US workers.  To be sure, most CIOs turn to foreign talent for highly specialized IT skills rather than cost savings. Top-tier talent helps companies — from banks and retailers to healthcare and aerospace companies — innovate and boost revenues. This, in turn, fuels broader economic gains for both the company and the country. The American Immigration Council reports that immigrants or their children founded 46% of all Fortune 500 companies. In 2023, these firms generated $8.6 trillion in revenue and employed over 15 million people worldwide.  “Restrictive policies choke the supply of niche skill sets that domestic pipelines can’t fill at scale,” states Patrice Williams-Lindo, CEO of Career Nomad and a former senior leader at Deloitte and KPMG. Curtailing immigration also creates incentives for CIOs to over-automate and push remaining staff past the breaking point, she argues.  Related:Bentley Systems CIO Talks Leadership Strategy and AI Adoption This isn’t to say that there isn’t room for improvement. Some companies, particularly IT staffing firms, have manipulated and abused the H1-B system, and some so-called “essential” workers aren’t so essential. There’s also a fundamental problem with the way the H1-B lottery takes place. Anyone can apply — so the highest-skilled workers don’t necessarily prevail. Some firms have flooded the system with applicants.  Yet these problems don’t negate the value of foreign workers in the US economy. Research shows that the H-1B labor force complements US workers rather than displacing them. “There has been a lot of emphasis on STEM education in K through 12,” says Julie Gelatt, associate director of the US Immigration Policy Program at the Immigration Policy Institute (MPI). “But the underlying demographics do not support the notion that the US can produce enough people with the required skills,” she says.  Green Cards, Red Tape A shortfall in homegrown talent might be manageable if the US had a tangible strategy for filling the gap. Unfortunately, a lack of training programs, technical institutes, and a general disinterest in STEM careers don’t bode well. “The number of people admitted to the US on high skill visas is perpetually short of the demand,” says Giovanni Peri, a professor of economics at the University of California, Davis, who studies labor issues.   Related:Empathy: The Strategic Differentiator for CXOs in Tech The current cap on H1-B visas is 85,000 per year, a number that hasn’t changed since the program launched in 1990 — despite population growth and huge changes to the economy. For fiscal year 2025, USCIS reported receiving nearly 480,000 registrations for the lottery, which translates to an 18% acceptance rate. In addition, there’s currently a backlog of 1.8 million green card applicants.   Reforms have floundered. In December 2024, the Biden Administration finalized a rule to revamp the selection process and modernize H1-B rules. This included tightening eligibility, addressing fraud and making the process more equitable. Earlier ideas — such as prioritizing applicants based on the highest wage levels — sparked controversy over potential harms to small businesses. While USCIS continues to use a random selection lottery that rewards volume over merit, the Trump administration has revised the idea of basing H1-B visas on wages. In mid-August 2025, it reportedly proposed a rule change.  Work in Progress Perhaps it may be difficult to see what comes next, but CIOs must develop a plan. Immigration restrictions pose a fundamental risk to talent pipelines, workforce stability, and future innovation. Meanwhile, the United Kingdom, Canada, Australia and other countries are turning America’s problem into an opportunity by actively courting foreign scientists, researchers and tech workers with streamlined visa programs and startup-friendly policies.  Loren Locke, an immigration attorney based in Atlanta, urges CIOs to fully embrace high-value employees who choose to self-petition for green cards under EB-1A or National Interest Waiver (NIW) categories. “CIOs can support this by helping them build qualifying case profiles,” she says. This includes highlighting articles, books, patents, conference appearances, and other signs of expertise. At the same time, it’s essential to provide internal mentorship and legal guidance, she adds.  Mitigating uncertainty and volatility is crucial, Le says. A big piece of the puzzle is establishing a comprehensive IT staffing and immigration strategy. This includes directly connecting digital initiatives with immigration. “CIOs must align their strategies with CHROs