Guiding AI Adoption in SMB: How Boards and Advisors Can Accelerate Value Through External Expertise
Artificial intelligence (AI) has rapidly become one of the most transformative forces in modern businesses; redefining competitive advantages and creating new pathways for growth. Yet, for small and mid-sized companies, the leap from curiosity to implementation can be steep.
While large enterprises can afford in-house data teams, experimentation budgets, and AI transformation offices, smaller firms must balance ambition with reality. They face real-world challenges: limited capacity, operational constraints, fragmented data, and uncertainty about where to start.
This is where Boards and Advisors can play a pivotal role — not by mandating AI adoption, but by guiding how it happens. By helping management identify and connect with external expertise, boards can ensure that AI initiatives are strategic, sustainable, and value-creating rather than reactive or experimental.
The Leadership Gap in AI Adoption
For many smaller organizations, the primary obstacle to AI isn’t a lack of interest — it’s a lack of structure.
Operational Readiness: Deploying AI touches nearly every part of the organization — data, processes, people, compliance, and governance. Most firms underestimate the foundational work required before any model can add value.
Strategic Ambiguity: It’s easy to chase buzzwords. Without a defined purpose or measurable goals, AI efforts often become scattered or symbolic.
Execution Challenges: Even with a solid idea, few smaller companies have the in-house expertise to move from concept to production-level integration.
Resource Constraints: Building a permanent AI team can be prohibitively expensive and unnecessary at early stages.
Boards and advisory groups often see these challenges repeated across multiple portfolio companies. Their cross-organizational perspective positions them uniquely to recognize patterns, identify gaps, and broker solutions that individual management teams might overlook.
Why External Expertise Makes Sense
Introducing specialized outside support — whether through consultants, operating partners, or interim executives — gives companies a practical bridge between strategy and execution.
1. Objective Assessment and Diagnosis
An external perspective can help management evaluate their true readiness. Before investing in tools or hiring data scientists, an experienced advisor can clarify what’s needed, what’s premature, and where early value can realistically be captured.
2. Strategic Alignment with Business Goals
AI should never be treated as a project separate from the business strategy. External experts can help align initiatives with customer needs, financial outcomes, and organizational capabilities — ensuring AI supports the mission rather than distracts from it.
3. Execution Discipline
Translating strategic intent into tangible change requires operational precision. Experienced partners bring frameworks, templates, and governance models that prevent wasted effort and ensure measurable progress.
4. Capability Transfer
The best external relationships build internal strength. When used effectively, outside partners accelerate the learning curve, helping company teams understand what’s possible while developing their own operational competence.
5. Cross-Industry Insight
Advisors with exposure to multiple sectors often recognize patterns early. They can introduce proven approaches and warn against pitfalls encountered elsewhere, giving smaller firms a competitive edge.
Boards can play a catalytic role here — not by “doing” the work, but by facilitating access to people who can.
How Boards and Advisors Can Help
Effective governance around AI doesn’t mean micromanaging projects. It means ensuring clarity, capability, and accountability. Here’s how boards and advisors can actively shape that journey:
1. Set the Strategic Context
Boards can help management articulate why AI matters for the business. Is it a growth driver? A risk mitigator? A way to enhance efficiency or customer retention? Framing AI within the company’s broader mission keeps initiatives focused and credible.
2. Encourage Evidence-Based Readiness Assessments
Rather than rushing toward technology investment, boards can prompt leadership to assess data quality, workflow maturity, and cultural readiness. A clear-eyed diagnostic prevents waste and identifies realistic priorities.
3. Facilitate Introductions to Qualified Experts
Boards and advisors often have deep networks — including operating partners, subject matter specialists, and transformation consultants — who can be matched to the company’s scale and needs. Making these introductions can compress timelines and reduce risk dramatically.
4. Ensure Governance and Ethics Are Embedded
AI introduces new risks around bias, privacy, and transparency. Boards are responsible for ensuring governance frameworks evolve alongside technical capability. External experts can help design and audit these structures effectively.
5. Monitor Progress Without Overreach
The board’s role is to ensure that AI initiatives are producing measurable results and remain aligned with strategy — not to manage implementation. Regular progress reviews with clear KPIs allow oversight without interference.
6. Promote Long-Term Capability Building
Ultimately, AI maturity should not depend on permanent outside help. Boards can encourage management to treat external partnerships as accelerators, not crutches — transferring knowledge to internal teams over time.
A Pragmatic Roadmap
When boards or advisors help guide this process, companies can adopt a structured, five-phase approach:
Listen and Define the Inflection Point – Understand why AI is relevant now and what outcome defines success.
Assess and Diagnose – Evaluate data readiness, process maturity, and business opportunities.
Design the Strategy – Identify where AI creates value and how it fits into operations.
Execute with Agility – Pilot, learn, and scale with clear metrics.
Embed and Institutionalize – Make AI part of the business fabric, not a one-time project.
Boards can ensure management moves deliberately through each stage — learning as they go and measuring results at every step.
The Bigger Picture
AI adoption isn’t just a technology decision; it’s an organizational evolution. For small and mid-sized companies, success hinges on how intelligently they mobilize limited resources — and how effectively leadership teams leverage outside experience.
Boards and advisors sit at the intersection of oversight and opportunity. By introducing external expertise and supporting disciplined execution, they can help their companies navigate complexity, build confidence, and unlock the real value of AI.
The outcome is not just smarter systems — but smarter organizations: more data-driven, resilient, and strategically aligned with the future of their industries.
Gene Zulkuski, Partner