Outsider Insights | Agentic AI: What CEOs Need to Know Before They Invest

Outsider Insights

Across Chief Outsiders, we talk to hundreds of CEOs every month. In this series, we explore the trends and challenges we’re hearing from these discussions – and what you can do if you’re facing the same issues in your business.

Agentic AI: What CEOs Need to Know Before They Invest  

In recent conversations with CEOs, one question keeps surfacing: “Should we be incorporating AI into our growth plans?”

The short answer: probably — if you’re clear on why and what outcome you expect.

The good news? Many CEOs are asking the right questions. They’re not asking:

• “Should we use GenAI or Agentic AI?”

• “What model stack should we deploy?”

• “Which framework is best?”

They’re asking:

• “How should we be using AI in marketing?”

• “Can AI make our sales team more productive?”

• “How can AI amplify our growth plans?”

That’s important. It shows they care about business impact — not just technology adoption.

But here’s the nuance: the answer to “How should we use AI?” sits on a spectrum. On one end is AI that assists people. On the other is AI that operates more independently.

Understanding where you are on that spectrum — and where you should be — is the strategic conversation.

Why This Matters — For You and Your Customers

Your buyers are already using AI.

AI-driven research is reshaping how buyers find and evaluate options. They’re asking AI tools to find and compare vendors, summarize solutions, and narrow shortlists before your sales team even knows they’re in-market.

Case in point: Traditional SEO still matters, but companies are increasingly being filtered through AI-generated summaries. If your digital presence is inconsistent or thin, you may be eliminated before a human conversation ever starts.

The right AI system can facilitate and accelerate good internal processes.

In the right workflow, AI agents can reduce bottlenecks, improve visibility, and accelerate response time – but only if:

• Your data is clean

• Your processes are defined

• Your team understands where human oversight is required

Automation doesn’t create discipline. It scales whatever discipline - or dysfunction - already exists.

Gen AI vs. Agentic AI

Another thing to consider is that not all AI is the same.

Many companies are already using Generative AI in some way. Marketing teams use it to draft content. Sales teams use it to summarize calls. Leaders use it to analyze documents.

These are largely reactive use cases. You prompt it. It responds.

Agentic AI is different.

Instead of responding to prompts, agentic systems pursue defined objectives. You assign a goal, and the system can take multiple steps to support it — pulling data, generating insights, initiating actions, and adjusting along the way.

For example:

• A traditional Gen AI tool drafts an email based on a prompt.

• An agentic system monitors campaign performance, flags declining engagement, suggests changes, and initiates testing.

The technology is real – as is its promise. But it’s not plug-and-play, and results will vary based on organizational readiness.

Where Agentic AI Can Fail Without Organizational Readiness

Gartner predicts that more than 40% of agentic AI initiatives will be canceled by 2027 due to unclear business value or weak risk controls. That’s not a tech failure. It’s a strategy failure.

• AI is adopted because it’s trending, not because a business problem was defined.

• Poor data quality becomes amplified at scale.

• AI is layered onto broken processes.

• Leadership measures “AI usage” instead of revenue impact.

AI doesn’t fix broken systems. It magnifies them.

The Readiness Test

Before investing in any AI initiative - especially agentic systems - ask three questions:

1. Is your data and process discipline strong?
AI amplifies what already exists. If data is unreliable or workflows are inconsistent, automation will scale the problem.

2. Can you clearly define the problem?
“We should use AI” isn’t a strategy. “Our lead response time is 18 hours and we’re losing deals” is a defined problem that automation might address. Start with friction. Not technology.

3. Is there human oversight and judgement?
AI systems can make mistakes or poor decisions. Without monitoring, risk compounds quickly.

If the answers to these questions aren’t clear, your constraint isn’t AI. It’s operational readiness.

What You Can Do This Quarter

To help your team prepare to benefit from the promise AI, especially agentic AI, offers, start with three practical moves:

1. Audit how you show up in AI-driven research.
Ask ChatGPT, Claude, or Perplexity about your product category, as well as your company and competitors. If the answers are thin or inaccurate, fix your digital presence.

2. Map your growth workflows.
Where do deals stall? Where is visibility weak? Where do handoffs break? That’s what needs to be fixed before it’s scaled with AI – and it’s where AI may create leverage.

3. Build internal literacy.
Your leadership team doesn’t need to be AI technology experts. They do need to understand what AI can and cannot do — and where it creates measurable advantage.

The Real Risk Isn’t Moving Too Slowly

The real risk is adopting technology because it’s on trend, not because it solves a defined problem.

Most companies — including your competitors — are already using AI in some form. Some are experimenting with agentic systems. The differentiator for those that thrive with AI won’t be speed. It will be preparation.

Because growth doesn’t come from adopting AI. It comes from solving real problems — whether that requires new technology or better discipline around what you already have.

If your data is clean, your strategy is clear, and you’ve identified workflows where autonomy creates measurable value. That’s when AI becomes a growth lever.