Agentic AI has moved from roadmap item to operating reality. For enterprise leaders, the question is no longer whether to use AI agents. The harder questions are about value, accountability, security and the workforce. This article covers six of those questions, with the latest data and practical questions to take back to your team. Each one is also a session topic at the 2026 WLDA Summit at the New York Stock Exchange on October 30, 2026.
What is agentic AI?
Agentic AI refers to AI systems that can pursue a goal with some independence. They plan steps, use tools and software, and take actions, rather than only answering a prompt. A chatbot drafts an email when you ask it to. An agent might triage the inbox, draft the replies, update the CRM and flag exceptions for a person to review. That extra autonomy is what makes agents valuable. It is also why they raise new questions about oversight.
Agentic AI by the numbers
- 40% of large enterprises are now scaling AI agents, up from 27% a year earlier. Yet only 37% of respondents attribute any EBIT impact to AI, about the same as last year. (McKinsey, The state of AI in 2026)
- 40% of enterprise applications will include task-specific AI agents by the end of 2026, up from less than 5% in 2025. (Gartner)
- 15% of day-to-day work decisions will be made autonomously by agentic AI by 2028, up from 0% in 2024. (Gartner)
- Over 40% of agentic AI projects will be canceled by the end of 2027, because of rising costs, unclear business value or inadequate risk controls. (Gartner)
- Only about 130 of the thousands of vendors marketing agentic AI offer the real thing, by Gartner’s estimate. It warns about “agent washing,” where existing chatbots and automation tools are rebranded as agents. (Gartner)
- 71% of corporate directors say their boards need stronger AI skills for effective oversight. 82% rate the information linking AI outcomes, risks and business performance as fair, poor or not provided. (PwC 2026 Annual Corporate Directors Survey)
Put together, the numbers tell a clear story. Adoption is accelerating, but value, governance and board readiness are lagging behind. Closing that gap is the leadership agenda for 2026.
1. Where is agentic AI creating real business value?
Pilots are easy; production is hard. With fewer than four in ten organizations reporting any EBIT impact from AI, the leaders who stand out are the ones who tie agents to specific business outcomes rather than to experiments. At the Summit, Asha Saxena, Founder & CEO of WLDA, opens with The Agentic Enterprise: Leading Through the Next Shift in AI. Later, Ankor Rai, CEO of Straive, presents AI in Action: Scaling Enterprise Transformation.
Questions to ask your team:
- Which three workflows would move a P&L line if an agent handled them end to end?
- What does success look like in numbers, and who owns that number?
- Which pilots should we stop funding?
2. How are the capital markets reading AI?
Investors increasingly judge companies on the credibility of their AI strategy, not just its ambition. Tara Dziedzic, Head of US Listings at the New York Stock Exchange, speaks on AI and Capital Markets. It’s a fitting session for a Summit held inside the exchange.
Questions to ask your team:
- Can we explain our AI strategy in two sentences an investor would find credible?
- Which AI metrics are we prepared to report externally?
- Are our AI claims backed by results we can show?
3. What are the major AI platforms building next?
With Gartner predicting that 40% of enterprise apps will include task-specific agents by the end of this year, much of the agentic future will arrive inside software companies already use. The AI Leaders: Products, Platforms & Possibilities session brings together Anthropic, Google, Amazon and Microsoft.
Questions to ask your team:
- Which agent capabilities will our current vendors ship this year, and do we need to build any ourselves?
- Is our data accessible, clean and governed enough for agents to use?
- How do we avoid paying for “agent-washed” products?
4. What do boards need to know about AI?
Seven in ten directors say their boards need stronger AI skills, and most say the information they receive on AI is inadequate. The AI in the Boardroom panel takes this on. It features April Galda Joyce (Symetra & Essent Group), Suzanne Brown (NYSE Board Services), Denise Leonhard (Zelle) and Natalia Shuman (MISTRAS Group).
Questions to ask your team:
- What AI reporting does our board receive, and does it connect AI to risk and business performance?
- Which board committee owns AI oversight?
- What AI education would help our directors most?
5. How does the C-suite lead the transformation?
Scaling AI is as much an organizational challenge as a technical one: funding models, operating structures and the skills teams need to work alongside agents. Gartner expects at least half of knowledge workers to develop new skills to work with, govern or create AI agents by 2029. Gary Brantley (NFL), Sastry Durvasula (TIAA), Susannah Greenberg (L’Oréal) and Rashida Jones (Uncensored) join the C-Suite Leadership Panel: Leading Enterprise Transformation in the Age of Agentic AI.
Questions to ask your team:
- Who is accountable for AI outcomes across the business, not just in IT?
- How will roles change when agents take on routine work, and what’s our reskilling plan?
- How do we fund AI past the pilot stage?
6. How do you build trust in autonomous systems?
Inadequate risk controls are one of the three reasons Gartner gives for canceled agentic AI projects. For boards, cybersecurity, data privacy and IP risk top the list of AI concerns. When agents act on their own, security and governance become leadership issues. Ken Phelan (Gotham Technology Group), Ankur Shah (Straiker) and Larry Zelvin (BMO Financial Group) lead the Risk, Security & Governance Panel: Building Trust in the Agentic Enterprise.
Questions to ask your team:
- What is an agent allowed to do without human approval, and who decided that?
- How do we monitor, audit and roll back what an agent did?
- Have we tested our agents against misuse and manipulation?
A quick readiness check for leaders
Before scaling agents, check that you can answer yes to most of these:
- We have a short list of agent use cases tied to measurable business outcomes.
- Our data is accessible, well-governed and fit for agents to act on.
- Every agent has a named business owner and defined limits on what it can do alone.
- We can monitor, audit and reverse agent actions.
- Our board gets regular AI reporting that connects AI to risk and performance.
- We have a plan for how roles and skills will change.
Join the conversation on October 30
The 2026 WLDA Summit runs 8:00am–4:00pm at the New York Stock Exchange, 11 Wall Street. It features two Next Generation AI Innovation Showcase sessions and ends with the NYSE Closing Bell. The WLDA Awards Gala follows at 6:00pm at 48 Wall Street. New to the Summit? Read What Is the WLDA Summit? Why the 2026 Summit at the NYSE Matters.
Frequently asked questions
Agentic AI refers to AI systems that can pursue goals with some independence. They plan steps, use tools and take actions, rather than only responding to prompts.
Gartner predicts that over 40% of agentic AI projects will be canceled by the end of 2027, because of escalating costs, unclear business value or inadequate risk controls.
According to McKinsey’s State of AI in 2026 survey, 40% of respondents from large organizations report scaling AI agents, up from 27% the year before.
PwC’s 2026 directors survey found that 71% of directors say their boards need stronger AI skills, and 82% say information linking AI to risk and performance is fair, poor or not provided.
The 2026 WLDA Summit on October 30, 2026 at the New York Stock Exchange focuses on agentic AI leadership for CDOs, Chief AI Officers, CIOs, CTOs and board directors.
