Rushed AI initiatives can swiftly expose neglected tech strategy flaws and data infrastructure gaps. The pattern is predictable — companies tout technologies to pacify real or perceive board expectations or outfit executive vanity projects, while control prerequisites languish and employee angst balloons.
That’s why boards and c-suites must ask the right AI readiness questions to foster the responsible governance that digital strategy acceleration requires.
KPMG’s 2025 Q3 2025 AI Pulse Survey found that 82% of executives identify data quality as the primary AI success barrier — up from just 56% last quarter. Despite the readiness gap, 78% of leaders admit “pressures to demonstrate value to investors or their board is a critical factor influencing their GenAI strategies in the next six months.”
That creates tension between the need for quick wins and the reality of AI’s transformative benefits, especially when 78% also said that legacy metrics don’t capture AI impact. Meaningfully tackling these high-stakes challenges will determine whether boards forge AI-ready futures or casually preside over adrift, pricy tech experimentation. Three questions can shift that trajectory:
- Can we trust our data infrastructure for AI agent deployment?
- Do AI performance measures reflect tomorrow’s success factors?
- Does our AI agenda aim to build the future or fix the past?
With reliable answers, boards can responsibly advance vital AI agendas.
Must Trust
“AI can’t deliver trusted outcomes without trusted data,” said KPMG International’s global head of advisory and U.S. advisory vice chair Rob Fisher who summarized the timely research incisively, succinctly and poignantly.
While 55% of the surveyed enterprises pilot AI agents, less glamorous data governance, system integration and IT modernization work can’t be deferred nor underestimated. Despite massive Q3 AI investments averaging $130 million each, 42% have deployed AI agents despite acknowledging the need to modernize and optimize data quality.
“It is a significant challenge because many organizations have fragmented data, scattered across various systems, hindering consolidation efforts and making it harder to gain a comprehensive overview. This unfortunately buries key business insights within disparate datasets, making them difficult to access and analyze effectively,” Fisher emphasized.
“As the jump in the survey underscores, there is an increasing recognition from the most senior leaders at our clients that it’s imperative to modernize their data and put responsible AI and data governance in place,” Fisher added.
Notably, 71% of surveyed organizations also characterized agentic system complexity a major “deployment challenge.” It’s not just poor outcomes that could result. Layering autonomous AI agents on shaky data foundations fuels systems too complex to govern, too opaque to audit and too risky to trust.
That’s especially worrisome if KPIs don’t mirror “big bet” aims and objectives.
Modern Measures
“Traditional ROI metrics don’t capture the full picture and most leaders know it,” Fisher warned. Conversely, he advised, “The key is to adopt a new portfolio view of value creation, instead of focusing on a single ROI number, leaders should track dynamic indicators across the business.”
A portfolio view can drive immediate cost reductions, capacity gains and long-tail conversion benefits — such as unlocking supply chain efficiencies or accelerating financial closes. All improve cash flow and resource forecasting — and, ultimately, competitive edge.
To start, he suggested executives identify “outputs that can be quantified within traditional ROI frameworks.” For instance, Fisher cited, “Today, leaders are already tracking improved productivity (97%), enhanced profitability (94%) and higher quality work (91%).”
“We’ve been working with a few dozen clients globally in industries such as consumer & retail, energy, banking and others to help them with their financial close processes to drive faster close cycles. We’ve heard from them that it’s freeing up time for higher level work and innovation, while improving accuracy, and reducing costs,” Fisher shared.
The framework is sensible, but requires steadfast strategic clarity, purposeful measurement and board patience — none often sits neatly with quarterly pressures, particularly as AI-era employee trust and workplace culture teeter.
Better Together
Fisher reinforced AI strategy’s irreplaceable human element. “Deploying agents is just the start. Success depends on preparing your workforce to thrive alongside them. The cultural changes required to successfully prepare your workforce for the pace of change cannot be underestimated,” he emphasized.
“While AI can accelerate and enhance how we work, it does not replace human expertise, experience and judgment. At KPMG, we’re training our people to use AI responsibly, and human oversight remains at the center of how we deliver trusted, high-quality work.”
“Our new American Worker Survey found that nearly 9 in 10 workers now use AI at least weekly, and half use it daily — up nearly 20 points from last year. The survey also found that 76% say they feel prepared to use AI in their roles, and 84% want more training to build skills. But interestingly, 52% worry that AI could eventually displace their jobs — nearly double last year’s figure.”
“Organizations must recognize this tension and seize the moment by reshaping workforce strategies now for an AI-driven future. That means planning for new skills and roles, guiding employees through change, and creating clear career pathways. There’s an opportunity to build employee trust through transparency as to how success and high performance might be redefined, how day-to-day work in many roles will change, where roles may be displaced, and what new roles are being created by AI,” Fisher suggested.
He enthusiastically shared that many clients are eager to re-design L&D and change management programs to prepare their AI-era workforce. That includes redefining future jobs, ensuring employee upskilling and offering digital “sandboxes” where employees can practice with AI agents. Advanced organizations are developing AI-era shadowing programs where employees observe experts working with agents, hone prompt engineering and foster a partnership mindset to human-bot collaboration. That’s a growth mindset.
Future-proofed
AI is unquestionably the future. Readiness is today’s imperative. Boards don’t need all the answers, but must expeditiously tap the digital era talent and expertise — in-house or externally — to mitigate risk, build trust and create value. That’s timely and timeless governance. Who’s building tomorrow?
