IDC opens the 2027 AI Leadership Summit and sets the agenda for the day

AI is no longer a CIO conversation. This opening panel brings together the executive triumvirate to explore how leaders are aligning on the AI investment thesis, the cost discipline and the value-attribution framework that protects funding when results lag, and how to bring the board along without waiting for directors to become AI experts.

Boards increasingly benchmark companies on revenue per employee. Line-of-business leaders debate how to balance new revenue creation with productivity gains, and how to set targets without breaking morale, talent retention or the employer brand as work shifts toward humans and AI agents operating side by side.

Will familiar change-management approaches still work when AI agents become digital colleagues? In this boardroom-style discussion, executives work through what to keep, what to modify and where AI fundamentally rewires how change is led across the workforce, from role design and skills to accountability and culture.

By 2028, IDC expects 100+ companies built predominantly using AI to generate $1B+ in revenue with fewer than a dozen employees. A founder shares the operating model behind an AI-native business: what is automated, what stays human, and what established enterprises can borrow from it.

How finance leaders are rebuilding cost models, ROI frameworks and FinOps practices for AI, from token economics and consumption costs to defending investment when productivity gains lag. With AI governance the #2 investment priority for 28% of organizations in 2026, this roundtable asks how to keep the AI P&L defensible to the board.

As AI begins to manage workflows, approve decisions and sit alongside people in teams, the people function faces its biggest redesign in a generation. HR and business leaders compare approaches to role design, reskilling and the governance of hybrid human-agent teams.

Operations and supply chain leaders share how they are moving from AI-assisted tasks to autonomous, agent-driven workflows, including the guardrails, exception handling and accountability models that survive production reality.

Autonomous agents need real-time, trusted and well-governed data. While 83% of organizations have increased their focus on data management since generative AI emerged, IDC expects those that fail to prioritize AI-ready data to face a 15% productivity loss versus peers by 2027. IT and data leaders share how they are closing the gap.

Enhancing automation beyond manual tasks is the top strategic priority for agentic AI in the US (55%), while hyper-personalization ranks lowest (28%). Customer service, marketing and sales leaders discuss how to move from efficiency gains to revenue-generating use cases.

Centralized control keeps AI coherent but slows it down; full federation moves fast but fragments accountability. In this boardroom-style workshop, executives work through where to draw the line on ownership, how to embed compliance, ethics and cost control into AI operations, and how to govern bottom-up shadow AI without smothering it. IDC expects every Global 100 firm to spend at least $2M a year on unified AI governance by 2028.

As agents become primary users of enterprise applications, architecture choices become strategic business decisions rather than back-of-house IT. IDC expects 45% of Global 500 enterprises to require headless, composable architectures by late 2027. This session looks at moving from disconnected AI investments to a coordinated operating model guided by a business architecture.

IDC expects 65% of build-your-own agentic AI projects to be abandoned by 2028 for failing to meet ROI goals. This session shows how enterprises keep agentic initiatives from collapsing under their own ambition, from scoping and cost control to accountability for outcomes.

Manufacturing leads agentic AI adoption, with 52% of organizations holding established spending plans. A manufacturing operations leader shares what it takes to deploy AI in a real factory environment, how OT and IT converge, and the change-management lessons that apply to every operations leader.

63% of organizations are more likely to adopt digital sovereignty solutions for AI workloads. This session explores how regulators are thinking about AI governance, sovereignty and accountability, and how forward-leaning enterprises increase their focus on sovereignty without creating a compliance bottleneck.

IDC analysts and executives debate how productivity should be measured across every business function as AI matures. The panel closes the day by connecting the threads of investment thesis, governance, architecture and operating model to the board-defensible outcomes that decide which AI strategies earn long-term confidence.

IDC closes the day and summarizes the key takeaways for U.S. executives: how to govern AI, scale beyond the pilot trap, place the right bets on agentic and sovereign AI, and measure AI value.