I’ve sat through dozens of board meetings where technology comes up as an agenda item. The pattern is almost always the same. The CTO or CIO presents. There are slides about infrastructure, cybersecurity posture, maybe a digital transformation update. The board asks about budget. Someone asks if we’re “doing AI.” The CTO gives a diplomatic answer. Everyone moves on.
The problem isn’t that boards don’t care about technology. Most do. The problem is that they’re applying the wrong mental models to evaluate it, asking the wrong questions, and making investment decisions based on frameworks that worked for physical assets but fail completely when applied to software and data.
The Fundamental Mistake
Most boards evaluate technology the way they evaluate real estate. Cost per square foot. Depreciation schedules. Capex versus opex. Useful life calculations. Annual maintenance budgets as a percentage of asset value.
This makes sense for buildings. A building depreciates on a predictable curve. You know roughly what maintenance will cost. The asset doesn’t fundamentally change what it can do over time.
Technology doesn’t work like that. Technology either compounds or it rots. There’s very little in between.
A well-architected data platform doesn’t just sit there holding its value. It enables new capabilities over time. Each new data source added makes the whole system more valuable. Each new analytical capability built on top of it creates options that didn’t exist before. The marginal cost of the next insight drops as the platform matures.
A neglected data platform does the opposite. It accumulates technical debt. Integrations break. The team spends more time maintaining it than extracting value from it. Eventually, it becomes a liability – too expensive to maintain, too risky to replace, and too brittle to build anything new on top of.
Boards that treat technology investment as a depreciating asset will consistently underinvest in maintenance, overinvest in shiny new projects, and wonder why their technology capabilities never seem to mature.
The Wrong Questions and the Right Ones
Board members are trained to ask probing financial questions. That’s their job. But when it comes to technology, the questions they’ve been trained to ask often miss the point entirely.
Boards ask: “What’s the IT budget?”
This tells you almost nothing useful. A $20 million IT budget could mean an organisation with world-class technology capabilities, or it could mean an organisation haemorrhaging money on legacy systems and consulting fees. The number alone doesn’t differentiate between spending that creates capability and spending that merely keeps the lights on.
A better question: “What percentage of our technology spend goes to running existing systems versus building new capabilities?” If 80% of the budget is keeping old systems alive and 20% is invested in growth, you’ve got a problem. The ratio tells you far more than the total.
Boards ask: “Can we cut this?”
Every technology budget line can be cut. The question is what capability you lose when you cut it. Boards rarely ask the follow-up: “If we reduce this investment, what can we no longer do? What takes longer? What breaks?”
A better question: “What capability does this investment give us that competitors don’t have?” If the answer is “nothing – it just keeps us at parity,” that’s important to know. If the answer is “this is the system that lets us price 40% faster than the market,” cutting it looks very different.
Boards ask: “What’s the ROI on this project?”
ROI calculations on technology projects are frequently fiction. Not because people are dishonest, but because the benefits of technology investments are often indirect, delayed, and difficult to attribute. A new data warehouse doesn’t generate revenue directly. It enables the analytics team to identify a pricing opportunity that generates revenue. Attributing that revenue back to the warehouse investment requires a chain of assumptions that can be made to support whatever conclusion you want.
A better question: “What decisions will we be able to make with this capability that we can’t make today?” Decision-enabling framing is more honest and more useful than fabricated ROI calculations.
The Vendor Presentation Trap
This one is particularly insidious. A board member sits through a polished presentation from Salesforce, ServiceNow, or Microsoft. The slides are beautiful. The customer testimonials are compelling. The demo shows a seamless product that solves exactly the problem the organisation has been struggling with. The board approves a seven-figure deal.
Eighteen months later, the project is over budget, behind schedule, and delivering a fraction of the promised value. The board is frustrated. The CTO is exhausted. And the vendor is already pitching the next module.
What happened? The purchase price was maybe 30% of the real cost. The remaining 70% was implementation, customisation, integration with existing systems, data migration, change management, training, and ongoing administration. None of that was in the vendor’s slides. None of it was in the board’s approval discussion.
Boards need to demand three-year total cost of ownership analyses before approving major technology purchases. Not the vendor’s version – an internal one, built by the team that will actually implement it. Include implementation consulting, internal staff time, training, integration development, data migration, and the ongoing cost of operating and maintaining the system. The number will be dramatically higher than the licence fee, and that’s the number the board should be evaluating.
Why “Digital Transformation” Budgets Fail
If your organisation has a project called “digital transformation” with a start date, an end date, and a fixed budget, it’s probably going to disappoint.
Not because transformation is impossible. But because framing technology capability building as a project with a defined completion point misunderstands what technology does in a modern organisation.
Technology is ongoing capability building. It doesn’t have an end date any more than hiring has an end date. You don’t “finish” becoming a data-driven organisation and then stop investing in data capabilities. You don’t “complete” your cloud migration and then stop optimising your cloud infrastructure.
The best-run companies don’t have transformation budgets. They have continuously funded technology capabilities with rolling investment horizons. They think in terms of capability maturity – where are we now, where do we need to be in 18 months, what investment does that require – rather than project completion.
McKinsey’s board-level research consistently shows that organisations treating technology as continuous capability building outperform those running it as a series of discrete projects. The project model creates stop-start investment patterns, loses institutional knowledge between phases, and encourages the kind of big-bang thinking that produces expensive failures.
What Good Board Technology Oversight Looks Like
Some boards do this well. They share a few common practices that aren’t complicated but require deliberate effort.
Quarterly Technology Risk Reviews
Not just cybersecurity. Full technology risk – including technical debt levels, key-person dependencies, vendor concentration risk, data quality issues, and capability gaps. Protiviti’s 2025 Global Technology Executive Survey found that technical debt alone is rated as a major burden by the majority of technology executives. If the board isn’t hearing about it, that’s a governance gap.
Direct CTO/CDO Access to the Board
In too many organisations, technology leadership’s perspective reaches the board only after being filtered through the CEO or CFO. This filtering almost always strips out the nuance and urgency that matters. The CTO says “we have a critical technical debt problem that will cost us $5 million to address and $15 million if we don’t.” By the time it reaches the board, it becomes “IT is requesting additional budget for infrastructure modernisation.”
Good boards give the CTO or technology leader direct presentation time at least quarterly. Not through the CEO. Directly. The same way the CFO presents financial results without the CEO intermediating.
Metrics That Tie Technology to Business Outcomes
Uptime is not a business metric. Neither is “number of incidents resolved” or “percentage of projects delivered on time.” These are operational metrics that tell you whether IT is functioning, not whether technology investment is creating business value.
Better board-level metrics: time-to-market for new products or features, customer acquisition cost (which technology directly influences), revenue per employee (a proxy for operational efficiency), and data-driven decision coverage (what percentage of major business decisions are informed by analytics versus gut feel).
If you’re a CEO or board member wanting to improve technology oversight, start by asking your CTO what metrics they’d choose if they could show the board three numbers that represent technology’s contribution to business value. The answer will be more informative than anything in the current board pack.
The AI Investment Question
Right now, boards across every industry are approving AI budgets. Some of these investments will generate extraordinary returns. Many won’t. And the boards approving them often can’t tell the difference.
The pattern is familiar to anyone who’s watched previous technology hype cycles. A new capability emerges. Vendors rush to market. Consulting firms publish breathless reports. Competitors announce initiatives. Board members read about it in the Financial Times and ask the CEO why their company isn’t doing it. A budget gets approved. A project starts. Value materialises slowly, or not at all.
Smart boards are asking different questions about AI investment:
- What’s our data readiness? AI is only as good as the data it’s trained on. If your data is fragmented, inconsistent, poorly governed, or trapped in legacy systems, AI will amplify those problems, not solve them.
- Do we have the talent? Not just data scientists – do we have the engineering talent to deploy and maintain AI systems, the product talent to identify high-value use cases, and the change management capability to integrate AI into existing workflows?
- What’s the expected ROI timeline? AI investments in internal operations can show returns in 6-12 months. AI investments in customer-facing products might take 18-24 months. AI investments in fundamental business model transformation could take 3-5 years. Is the board’s patience calibrated to the actual timeline?
- What are we not investing in to fund this? Every dollar going to AI is a dollar not going to something else. Is the trade-off explicit and deliberate?
The worst reason to invest in AI is “our competitors are doing it.” Your competitors might be doing it badly. They might be doing it well but in a context that doesn’t apply to your business. “Competitors are doing it” is not a business case. It’s peer pressure with a budget.
Building Technology Literacy at the Board Level
You wouldn’t appoint a board member to the audit committee if they couldn’t read a balance sheet. Yet boards routinely oversee technology strategy with members who have no technology background and no framework for evaluating technology decisions.
This doesn’t mean every board member needs to be a former CTO. But every board should have at least one member with genuine technology operational experience – not just someone who invested in tech companies or served on a tech company’s advisory board. Someone who’s built and shipped products, managed engineering teams, dealt with technical debt, and understands the difference between a vendor’s promise and operational reality.
For board members looking to build their technology literacy, the top CTO and technology leadership programs increasingly offer board-oriented modules. Understanding the basics of cloud architecture, data governance, and AI capabilities doesn’t require a computer science degree, but it does require deliberate investment in learning.
The Cost of Getting This Wrong
Boards that mismanage technology oversight don’t just waste money. They create competitive disadvantage that compounds over time.
The company that underinvested in data infrastructure in 2022 can’t deploy AI effectively in 2026. The company that approved a major ERP replacement based on a vendor presentation is two years into a project that’s over budget and still hasn’t delivered the promised benefits. The company that cut its platform engineering team to hit short-term earnings targets now can’t hire enough engineers to rebuild the capability, because good engineers won’t join a company with a reputation for technical underinvestment.
These aren’t hypothetical scenarios. They’re happening right now in companies with boards that treat technology as a cost to be minimised rather than a capability to be cultivated.
If you’re on a board, or you work with a board on technology strategy, the single most impactful thing you can do is change the framing. Technology isn’t overhead. It’s capability. And the board’s job isn’t to minimise the cost of technology – it’s to ensure that technology investment is creating durable competitive advantage.
That’s a fundamentally different conversation, and most boards haven’t had it yet.
Ben is a full-time data leadership professional and a part-time blogger.
When he’s not writing articles for Data Driven Daily, Ben is a Head of Data Strategy at a large financial institution.
He has over 14 years’ experience in Banking and Financial Services, during which he has led large data engineering and business intelligence teams, managed cloud migration programs, and spearheaded regulatory change initiatives.