What Technology Leaders Are Saying About AI Spending, Governance and the Future of IT

Reflections from the 2026 HMG Atlanta C-Level Technology Leadership Summit

By Alex Dukhovny, Chief Revenue Officer, IntraTEM

Last week, I had the opportunity to spend the day alongside technology leaders from across Atlanta and beyond at HMG Strategy’s 17th Annual Atlanta C-Level Technology Leadership Summit.

HMG framed the event around “Iconic Leadership: Leading Like the CEO of Technology,” and that idea stayed with me long after the panels ended.

The title may speak most directly to CIOs, CISOs and CTOs, but the underlying message applies much more broadly. Technology leadership today extends across the people responsible for security, infrastructure, applications, enterprise architecture, AI, operations, finance and the countless systems that keep modern organizations moving.

Regardless of title, technology leaders are increasingly being asked to think beyond technology itself.

They are being asked to think about business outcomes.

Technology leadership is becoming business leadership

One of the most noticeable things about the conversations at HMG was the language being used.

The discussions were not centered only on platforms, systems or technical capabilities. They focused on transformation, governance, talent, security, resilience, returns, accountability and the ability to create measurable business value.

Suresh Rangarajan, CIO of the Americas Materials Business at CRH, opened the day’s executive sessions with a conversation about leading with vision, velocity and purpose through enterprise transformation. Later, Paul Dangel, Head of IT PMO at Bose, explored what it takes to create alignment between IT, the business and the C-suite.

Different roles and different challenges, but the underlying message was similar. Technology cannot operate separately from the business it supports.

Building the team behind the technology

That became especially clear during the Iconic Leadership: How to Lead Like a CEO – Designing the Future Workforce panel, featuring Jay Ferro, Shaun Hunt, Renee Pearson and David Tepper, moderated by Jig Patel.

The conversation reinforced something that is easy to overlook when we talk about transformation: technology may enable change, but people are the ones responsible for making it work.

AI makes that particularly relevant. Adopting a new platform is one part of the investment. Organizations also need people who can learn new tools, adapt existing processes, and keep the rest of the technology environment moving while transformation is underway.

That makes workforce development, reskilling and leadership part of the economics of technology transformation, not separate from it.

AI value has to show up in the business

The conversation during the Harnessing Data, AI and Strategic Technologies to Drive Long-Term Business Performance panel brought another challenge into focus.

Saikrishna Adivi, Joshua Bauman, Venkata Parchuri, Rama Ryali and Kevin Jones, moderated by Viren Shah, explored the pressure technology leaders face to innovate while still improving efficiency and business performance.

What stayed with me was the focus on outcomes.

AI experimentation is exciting, but eventually technology leaders have to answer much more practical questions. Where is AI creating value? Which processes are improving? What does it cost? How are we measuring the return?

Those questions become increasingly important as experimentation turns into enterprise-wide AI spending.

Security is part of the business strategy

The afternoon’s Security Innovation as a Strategic Differentiator panel brought the same business-oriented thinking to cybersecurity.

Eric Aslaksen, Monique Hart, Stacy Hughes and Murtaza Nisar, moderated by Jason James, explored what changes when organizations view security as something that can enable the business rather than simply protect it.

That distinction matters.

Strong security can affect an organization’s ability to serve customers, operate in regulated environments, pursue new opportunities and adopt emerging technologies confidently. Cybersecurity may have its own leaders and specialists, but its impact reaches far beyond the security organization.

Drew Vanover’s discussion on building trust in autonomous security reinforced another reality: as AI changes the speed and scale at which technology operates, organizations will need to rethink how quickly their governance and security practices can respond.

Technology scales. Leadership still depends on people.

The final panel, Scaling Resilience: Visionary Tech Leaders on Innovation and Inner Balance, brought the conversation back to the people responsible for navigating all of this change.

Chintan Patel, Sushma Punuru, Joe Schleupner and Dr. Irene Thong, moderated by Hunter Muller, discussed resilience and leadership at a time when the pace of technological change continues to accelerate.

One idea stayed with me: technology can scale much more easily than human judgment can.

Automation scales. Compute scales. AI scales.

People still have to decide where all of it should take the organization.

And perhaps that is why another theme felt increasingly clear to me as the day went on: great technology leadership is a team effort.

We often talk about the CIO, CISO or CTO as the person leading transformation. But no meaningful technology outcome belongs to one title or one individual.

I was reminded of that even before the Summit began. At the HMG dinner the night before, an award recipient was unable to attend and a member of their team accepted the recognition on their behalf. Rather than diminishing the moment, Hunter pointed out why it was so fitting: the work being recognized was never the accomplishment of just one person.

That idea carried into the next day’s conversations. The right strategy matters, and the right technology matters. So does the right investment. But, so do the people around you who turn those decisions into outcomes.

The CIO cannot do it alone. Neither can the CISO, CTO, VP, director or any other individual IT leader. Successful transformation requires technology, security, finance, operations and business teams working toward the same outcome.

That may have been one of my biggest takeaways from the entire Summit.

Technology leadership may start with a leader, but meaningful technology outcomes are built by a team.

The Innovation Accelerator Panel and a bigger question about AI spending

I also had the privilege of joining Hunter Muller, Emily Heath of Glow and Benny Rosner of Chronom.ai on stage for the Innovation Accelerator Panel.

One of the ideas I wanted to bring into that conversation was a challenge I see becoming more common across enterprise technology.

Organizations have ambitious AI agendas. The budgets required to support those ambitions do not always grow at the same pace. That creates an important question for technology and finance leaders: Where will the money come from?

One option is to ask for additional budget. Another is to slow down the AI roadmap. But, there is a third option that deserves more attention: finding capital inside the technology environment the organization is already funding.

For many enterprises, years of changing vendors, contracts, users, locations, devices, applications and infrastructure have created opportunities to recover spend that no longer supports the business.

That is where disciplined Technology Expense Management becomes more than a cost-reduction exercise. It can become a funding strategy.

Before increasing technology budgets, understand what is already being spent

Most technology environments are constantly changing.

Employees join and leave. Offices open and close. Services are provisioned and disconnected. Applications are purchased. Cloud resources scale. Contracts renew. Devices move between users. Business priorities shift.

The challenge is that the financial governance surrounding all of that activity does not always change at the same speed.

Over time, unnecessary or inaccurate spending can accumulate across several areas.

Telecom and connectivity

Circuits may remain active after locations close or services change. Contracted rates may not always appear correctly on invoices. Services requested for disconnection can occasionally continue billing.

Individually, these issues may look small. Across a large enterprise, they can become significant.

Mobility

Mobile environments change constantly as employees join, leave, change roles or receive new devices.

Without continuous oversight, organizations can end up paying for zero-use lines, outdated plans, unnecessary features or devices that are no longer assigned appropriately.

SaaS

SaaS environments present a different challenge.

Organizations may accumulate overlapping applications, unused licenses, unnecessarily high license tiers or subscriptions that automatically renew before anyone evaluates whether they are still needed.

The information often exists. The difficulty is turning it into actionable visibility without requiring teams to manually assemble the answer every time someone asks.

Cloud

Cloud infrastructure introduces even greater variability.

Idle resources, oversized instances, unattached storage, unused environments and commitments that no longer match consumption can all contribute to unnecessary spending.

Cloud was designed to scale quickly. Without deliberate governance, the cost can scale just as quickly.

The difference between an audit and ongoing management

One of the assumptions we encounter frequently is that technology spending has already been addressed because an organization has completed an audit, uses a provider or has internal controls in place.

Those things matter. But technology environments do not stand still.

In one example from our own work, a top U.S. healthcare system already had an established TEM provider and had previously completed an audit.

After bringing in IntraTEM, the organization identified $1.67 million in annual savings and recovered an additional $268,000 in one-time credits within six months.

The opportunity existed because the environment continued changing.

Billing discrepancies varied by location. Services that had been approved for disconnection remained on invoices. Contracted rates did not always reach the final bill. Operational changes had occurred after the previous audit was completed.

That is an important distinction. An audit shows you what was happening at a particular point in time. Management is continuous. For technology and finance teams responsible for increasingly complex environments, that difference matters.

AI spending may become the next major governance challenge

The conversation becomes even more important as AI adoption accelerates. Traditional software spending is often relatively easy to define. Organizations purchase a certain number of licenses, assign them to employees and revisit the agreement at renewal.

AI spending can behave differently. AI tools and workloads can consume tokens, compute resources, APIs, cloud infrastructure and third-party services based on actual usage. Agentic systems may initiate additional workloads or interact with other systems without following the predictable economics of a traditional seat-based software agreement.

That makes visibility and governance especially important. As organizations move from experimentation to broader AI deployment, technology leaders will need to understand not only whether AI is creating value, but also what that value costs to produce.

Waiting until the technology has already scaled makes that conversation much harder. The better approach is to establish the financial and operational governance around AI early, while pilots are still becoming programs.

The same disciplines that organizations have learned to apply to telecom, mobility, SaaS and cloud environments will increasingly matter for AI spending as well: Visibility. Ownership. Optimization. Governance.

Visibility should not require an investigation

Another takeaway from conversations at the summit was that the visibility challenge facing technology organizations is more nuanced than it sometimes sounds.

It is not that experienced IT leaders do not know their environments. They usually do. The more interesting question is how difficult it is to produce the information required to make a decision.

Ask a seemingly straightforward question:

What are we spending across this category, across every business unit, compared with what we contracted for?

In some organizations, answering it means pulling data from several systems, reconciling exports, building spreadsheets and assigning talented people to investigate.

Eventually, the answer arrives. But if getting the answer requires a project, the visibility is not truly operational. That distinction matters because technology leaders are facing more questions, not fewer.

They need information that is current enough to guide decisions about renewals, budgets, optimization, security, AI investments and business priorities without repeatedly pulling their teams away from higher-value work.

That is where operational efficiency becomes just as important as cost control.

Technology leaders cannot scale judgment, so they need better information

The summit’s conversations around leadership and resilience brought another idea into focus for me.

Technology continues to scale. Automation scales. Cloud scales. AI scales. The amount of information available to leaders scales. But judgment does not.

Senior attention remains one of the most valuable and limited resources inside any organization.

Every hour an IT or finance team spends assembling information is an hour they cannot spend acting on it. That may be one of the most overlooked costs inside the modern technology environment.

Good technology governance should therefore accomplish more than identifying unnecessary expenses. It should make the truth easier to access.

Leaders should be able to understand what they are spending, why they are spending it, where risk exists and what opportunities they have to improve without commissioning a new investigation every time the question changes.

Funding innovation through operational efficiency

That ultimately brings me back to the idea that opened the summit: leading like the CEO of Technology.

To me, that does not mean every technology leader needs to become a CEO.

It means technology leaders are increasingly responsible for the same kinds of decisions CEOs and CFOs have always had to make.

• Where should we invest?
• Where are we wasting resources?
• What creates value?
• What creates risk?
• What can we improve before asking the organization for more?

AI makes those questions more urgent, but it did not create them.

Final Atlanta C-Level IT Leadership Summit Reflections

For years, organizations have accumulated complexity across telecom, mobility, SaaS and cloud environments. Technology Expense Management gives IT and finance teams an opportunity to bring greater visibility, governance and cost control to that complexity.

And increasingly, the value recovered from those environments can help fund what comes next.

That may be AI today. Tomorrow, it will be something else. The specific technology will continue changing. The responsibility to manage it wisely will not.

That was one of my biggest takeaways from HMG Atlanta. The future of technology leadership is not simply about adopting more technology. It is about creating the visibility, governance and operational efficiency necessary to invest in the right technology with confidence.

Congratulations to the 2026 HMG Global Leadership Institute Award recipients, Sai Adivi, Chintan Patel, Paula Wagner, Daniel Stuart and Dr. Irene Thong.

And thank you to HMG Strategy, Hunter Muller, and the technology leaders who shared their experiences and perspectives throughout the day.

I left Atlanta with plenty to think about, and even greater appreciation for the people being asked to lead organizations through one of the fastest periods of technological change we have experienced.

Keep reading on AI governance

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Why Agentic AI Is Outpacing AI Governance (And What IT Leaders Should Do About It)

Five gaps in governance, infrastructure, data, measurement and trust, where agentic AI is moving faster than the controls around it.

About the author

Alex Dukhovny

Executive Vice President, IntraTEM

 

Alex oversees IntraTEM’s support and sales teams with a single focus: making sure every client receives the level of service we promise. He sets the standard for how the organization engages with clients, holds teams accountable to that standard, and ensures the partnerships we build are delivering real, measurable value.