The Advisory Board Squeeze

How AI and tighter governance are shrinking the space for advisory boards

I’m a founder, intrapreneur, and former CIO rethinking governance for the one-person business, navigating sole accountability in the age of intelligent machines—informed by plenty of scar tissue. All posts are free, always. Paying supporters keep it that way (and get a full-color PDF of my book Human Robot Agent plus other monthly extras as a thank-you)—for just one café latte per month.

---

I wrote this piece for class 22 of ScaleUpNation‘s Board Program. Interested in participating in one of their next classes? Check out their upcoming webinar:

---

Art of Scaling’ Webinar by Menno van Dijk.

On the 22nd of April ScaleUpNation hosts a (free) webinar about ‘The Art of Scaling’ from a Board perspective.
ScaleUpNation has 300 plus alumni, all specialist in the ScaleUp world.
This webinar is for executives interested in ScaleUps.
Founders, Investors, Advisors, C-level and (future) Board members.

You can subscribe using this link:
https://lnkd.in/eSHqfAUR

Hope to see you on the 22nd of April at 13.00 CET/1.00 PM

---

AI can now do half of the advisory board’s job. The courts want governance boards to do the other half.

Advisory boards are squeezed between AI tools that produce strategic advice cheaply and governance boards absorbing oversight responsibilities. Only contextual judgment survives.

Here’s an uncomfortable question for anyone sitting on an advisory board:

What exactly do you offer that Claude and ChatGPT can’t?

Governance boards just received a legal nudge that feels less like guidance and more like a deadline. The EU’s AI Act (Regulation 2024/1689) requires accountability for high-risk AI systems by August 2026, and regulators are treating that accountability as a board responsibility. The timeline is public and fairly blunt: enforcement for high-risk systems begins on August 2, 2026.

When regulations set a date, boards eventually pay attention.

The advisory board model, meanwhile, is drifting into an awkward middle position. A host of AI models and tools are making some of the board’s traditional contributions cheap and immediate. Meanwhile, governance boards are absorbing the rest because liability travels toward whoever signs the documents. The advisory board isn’t disappearing. But the version many organizations still maintain looks suspiciously like a relic of the past.

Let’s walk through the pressure points.

The Compliance Stampede

Corporate governance has a curious rhythm. Boards move slowly until courts or regulators start writing opinions. That phase has begun for AI.

A 2025 Deloitte Global Survey reported that 66 percent of boards say they have limited or no AI expertise. The number itself isn’t shocking. Boards historically recruit for finance, operations, and regulation. Deep technical literacy rarely makes the shortlist. What changed is the expectation surrounding it.

The oversight principle is gradually expanding toward technological risks. Recent Delaware Court of Chancery rulings have clarified that directors must receive regular briefings on mission-critical technologies. AI is quietly joining that category. The message from the courts is simple: directors cannot claim ignorance about the systems shaping their company’s core operations.

On my side of the Atlantic, regulators went further and put a date on the obligation.

The EU AI Act entered into force on August 1, 2024. High-risk system obligations begin in 2026. Boards now have roughly one governance cycle left to figure out what responsible oversight looks like, and organizations are responding with predictable speed.

Board intelligence platforms are building AI tools directly into governance workflows. Vendors such as Diligent and Nasdaq Boardvantage now advertise automated briefings, document summaries, and preparation tools that reduce director reading time by as much as 60 percent and board preparation time by up to 80 percent.

Anyone who has sat through a board meeting recognizes the irony. The typical board pack runs well beyond 200 pages. AI can now summarize it in minutes. Whether that represents efficiency or an admission that those pages shouldn’t have existed in the first place remains an open question.

Either way, governance boards feel the pressure to develop internal AI competence quickly. Committees are being created. Charters are being updated. Recruiters are searching for directors who understand machine learning well enough to challenge management.

The baseline is shifting.

The Squeeze on Advisory Boards

Advisory boards historically filled a gap that governance boards could not.

Directors carry fiduciary responsibilities. That makes them cautious. Advisory boards had the freedom to think more experimentally. They offered specialized domain insight, industry connections, and candid feedback without legal exposure.

That arrangement worked because two things were scarce: information and perspective.

Both are changing.

General-purpose AI tools now produce credible strategic analysis in seconds. A founder exploring pricing models, market entry, or regulatory exposure can run several scenarios through a capable model before breakfast. The output isn’t always perfect—but neither are board members. Yet the marginal cost approaches zero, and the speed is astounding. The AIs do the job faster, cheaper, and—more often than not—better.

Advisory boards often justify their existence through the “external brain” function. The sparring partner. The person who sees patterns across industries. But ChatGPT, Claude, Gemini, Grok, and Perplexity now perform that role surprisingly well. And one only needs to visit the Product Hunt website to find a legion of AI-driven tools, such as SoloBoard, BoardOS, Foundora, aicofounder, AI debatearena, and Team Debate, eager to offer advice to startups and scale-ups at a mere fraction of the cost of an advisory board member lunch.

There’s even a free download available: Similar to the age-old Delphi Method, the LLM Council pattern is a multi-agent AI architecture where multiple LLMs collaborate like a council to produce more reliable answers through structured deliberation. The pattern enhances reasoning by leveraging diverse AI model perspectives.

Meanwhile, pressure also arrives from the other side. Governance boards are absorbing decisions that once lived in advisory territory. AI risk management, regulatory interpretation, and technical oversight increasingly sit inside fiduciary structures because the courts expect them there.

The accountability disappears upward.

The strategic advice vanishes downward.

The remaining territory for advisory boards becomes narrower by the day: decisions that require judgment shaped by experience, specific industry context, and relationships within and around the organization. That space still exists. It just looks smaller than it used to.

The Signaling Trap

Another dynamic deserves a less polite description. Let’s be honest: many advisory boards function as investor theater.

A skeptical analysis of AI advisory structures would describe them as human validation layers. A startup assembles recognizable names; investors notice the credibility signal, and the board rarely challenges management in any serious way. The advisors charge for their network and reputation, not their experience and insights. Everyone involved understands the arrangement.

The danger appears when executives believe their own marketing. A symbolic advisory board creates the feeling of strategic coverage without the substance of it. Founders assume someone is stress-testing the plan. Investors assume the same. In practice, nobody asks the hard questions. The technology sector is littered with the remains of startups and scale-ups that were guided off a cliff by theater directors.

Large organizations have, with varying success, experimented with external advisory councils to replace internal ethics groups. Governments have assembled high-profile AI advisory boards only to dissolve them months later when political pressure increased. The structures exist. The influence varies dramatically.

Advisory boards were originally intended as places for uncomfortable conversations. When they become branding devices, those conversations disappear.

The Surviving Species

So, what remains valuable about an advisory board?

Contextual judgment.

AI can produce information at extraordinary speed. Governance boards can impose accountability. Neither handles the messy space between them particularly well.

Consider the Techleap “AI Paradox” research covering the Dutch startup environment. The Netherlands has one of Europe’s highest concentrations of AI talent. Yet only 21 percent of its AI startups successfully scale, compared with 81 percent in the United States.

The problem is not information or technical expertise. The gap appears in decisions that connect technology, regulation, financing, and organizational design. Those choices rarely follow a formula. They depend on context that lives inside specific industries and networks.

This is where advisory boards can still matter.

Oxford Law researchers recently proposed an update to the business judgment rule, sometimes called “BJR 2.0.” Their argument is that directors now require cognitive adequacy to understand the technologies influencing corporate decisions. Technological literacy has joined financial literacy as a baseline competence.

Advisory boards operate in the layer above that baseline. They apply experience to situations where the playbook hasn’t stabilized yet. A founder deciding whether to launch an AI product under the EU AI Act. A scaleup balancing regulatory exposure against speed of deployment. An executive team confronting a market that changes every quarter.

AI produces the data. Governance boards enforce accountability. Advisory boards interpret the messy middle.

The organizations that recognize this distinction will keep their advisory boards small, specific, and uncomfortable enough to challenge assumptions. The rest will continue assembling impressive lists of names that rarely challenge directors’ decisions.

AI has reduced the cost of knowledge.

But judgment remains stubbornly human.

Jurgen Appelo, Solo Chief

---

A big thanks to yet another batch of new supporters of The Solo Chief. Cheers to Joshua Davis 🤝, Jerry Jensen, Mark S. Carroll, Heiko Braun, Dheeraj Sharma, Heller.urs@gmail.com, Joel Salinas, Elena | AI Product Leader, William Ferguson, Daniel Nest, Dennis Berry, Carsten Kiess, Scott Woods, XaB, and others whose accounts I can’t find. You all rock. Thanks for the coffee! ☕

If you support my work by upgrading to paid (it only costs you one coffee per month), I will send you a full, digital copy of my latest book, Human Robot Agent and I will invite you to private, one-on-one online meetups.

---

References

1. European Commission AI Act Service Desk. Timeline: Implementation of the EU AI Act. Available at: https://ai-act-service-desk.ec.europa.eu/en/ai-act/timeline/timeline-implementation-eu-ai-act (Accessed: April 2026).

2. Deloitte. Governance of AI: A Critical Imperative for Today’s Boards (2nd Edition). 2025. Available at: https://www.deloitte.com/global/en/issues/trust/progress-on-ai-in-the-boardroom-but-room-to-accelerate.html (Accessed: April 2026).

3. Ervin Cohen & Jessup LLP (ECJ Law). Delaware Expands Expectations for Board Oversight of Cybersecurity, by Jeffrey R. Glassman. January 20, 2026. Available at: https://www.ecjlaw.com/ecj-blog/delaware-expands-expectations-for-board-oversight-of-cybersecurity-by-jeffrey-r-glassman (Accessed: April 2026).

4. Nasdaq. AI for Boards: Governance Solutions. Available at: https://www.nasdaq.com/solutions/governance/boardvantage/ai-for-boards (Accessed: April 2026).

5. Techleap. State of Dutch Tech Report 2026. March 15, 2026. Available at: https://techleap.nl/reports/state-of-dutch-tech-report-2026 (Accessed: April 2026).