Every board packet these days includes an ambitious pitch for artificial intelligence (AI), yet few explain how that spend will convert into cash. Instead of clear financial baselines, directors are often handed slides focused on future capabilities and theoretical efficiency. For Bomsi Billimoria, the Founder & CEO of EvoXvantage, reading an AI proposal requires cutting through that narrative and looking directly at operational reality. Real oversight starts when the board stops evaluating software features and starts demanding verifiable business outcomes.
Grounding the Business Case in Real Numbers
Before a company commits to major new software, directors need a clear picture of what the current process costs today. Without that baseline, calculating return on investment turns into pure speculation. As Billimoria points out, “A well-structured AI business case ties the investment to one specific outcome the board can verify against real numbers, not to a technology capability.” When management cannot show the precise starting point, the delta they promise on paper is essentially meaningless. A solid proposal also makes an explicit distinction between tangible budget cuts and broad claims of efficiency. In practice, this means the pitch “separates hard savings, actual reductions in vendor spend, contract commitments, or headcount, from soft gains like productivity, and says out loud which is which.” Rather than writing an open-ended check, seasoned directors insist on funded checkpoints that require proof of value before the rollout expands. If a proposal cannot hold up when someone asks to inspect the underlying data, it simply is not ready for boardroom approval.
Finding Costs Hidden Between Departments
Software license fees are rarely the biggest expense in an enterprise rollout, yet they are often the only figure presented on the summary slide. Critical work like data cleanup and system integration gets pushed into general IT overhead, while retraining and change management end up sitting quietly in HR budgets. “Most business cases hide costs in the seams between departments,” Billimoria observes. These expenses are dispersed across different cost centers, so the true price of the initiative stays invisible to executive leadership. Individual business units frequently buy point solutions on their own corporate cards or departmental budgets without running them through a central system. “The board misses this because AI spend crosses finance, procurement, IT, operations, and legal, and each function reports its own slice as though it is the whole picture,” Billimoria explains. As no single leader reconciles these disparate contracts against the general ledger, the board only ever sees a fraction of the real outlay. Bringing discipline to the process means forcing management to build a comprehensive, cross-functional view of every dollar spent.
When management promises massive returns from newly automated workflows, directors have to dig into how those numbers were built. Specifically, Billimoria advises boards to “push back hardest on the productivity multiplier that never converts into an actual reduction in headcount or budget.” Hours saved during a workweek look great in a presentation, but they do not help the bottom line unless a line item shrinks. Boards should also challenge aggressive adoption timelines, because internal teams rarely transition to new platforms on day one without friction. Another common issue is the tendency for separate teams to claim credit for the exact same operational gains. When a tool touches customer service, operations, and billing at the same time, that single dollar of projected savings typically appears on multiple business cases. Directors must also check whether projected net savings account for ongoing maintenance, subscription growth, and vendor support fees. Catching these overlapping claims early stops the organization from funding projects built on inflated math.
Distinguishing True Utility From Presentation Polish
With regulators, investors, and auditors paying closer attention to corporate technology spending, boards face growing pressure to demonstrate real governance. A reliable way to test credibility is asking management to walk through their current workflow step by step before touching on the new software. “If they cannot explain the ‘as-is’ state with any precision, the business case is guesswork dressed up with a dollar figure,” Billimoria notes. A genuine operational plan includes data governance, security guardrails, and audit trails right alongside the financial projections. Credible proposals also prepare for the possibility that things might not go according to plan. While weak presentations only highlight ideal upside scenarios, thorough plans clearly outline what happens if adoption stalls or targets are missed. They assign specific executive ownership for the numbers, making it clear who answers for the investment if the gains fail to show up. Understanding downside risk gives directors the context they need to protect capital while still backing sensible innovation.
Most directors approve technology spending based on clean executive summaries rather than messy operational records. In Billimoria’s view, the single most critical step is asking management to open the books and show the baseline contracts. He suggests boards ask: “Show me, line by line, where this money is actually going today, and who signs off when the projected number does not show up.” Billimoria expects a meaningful share of the AI initiatives approved this year to miss their promised financial returns within 12 to 18 months, not because the technology fails but because nobody established a baseline to measure against. Boards that ask for the underlying ledger data now will see those gaps forming long before they become write-downs at year-end.”. By demanding verifiable facts over optimistic forecasts, directors can steer their organizations toward real operational value.
Follow Bomsi Billimoria on LinkedIn for more insights on AI business cases, board governance, and technology spending oversight.
