When Products Get Smart: What Board Directors Need to Know About Embedded Intelligence

As boards evaluate how AI is reshaping business strategy, one area often overlooked is the rise of embedded intelligence in physical products. The implications are more than just technical—they’re strategic, financial, reputational, and, increasingly, ethical.

Over the next 36 months, we’ll see a surge in smart, AI-infused physical products across every sector—from home appliances and industrial equipment to automotive systems and healthcare devices. This shift is being driven by small language models (LLMs) that are compact enough to run locally on-device, without relying on cloud infrastructure.

For directors, this isn’t a niche trend. It’s a signal that core product lines are about to evolve—possibly in ways that impact risk, revenue models, and customer trust.

1. Product Differentiation Becomes Intelligence-Driven

Historically, boards evaluated innovation through features, pricing, and competitive roadmaps. Now, the bar is being reset. Products that understand natural language, provide real-time support, or adapt to user behavior are no longer futuristic—they're imminent.

If your company’s competitors are embedding AI into their products and you’re not, the board should be asking:

"Are we doing enough to future-proof our product portfolio?"

Directors need to understand whether their teams are experimenting with small LLMs, what the timelines are, and how these capabilities can be incorporated without creating cost or complexity burdens.

2. Operational Risk Will Shift to the Edge

Embedding intelligence in physical products moves computation, data handling, and decision-making closer to the user. That’s a double-edged sword. While it improves latency, privacy, and independence from the cloud, it also introduces new categories of risk.

• What if the product malfunctions due to a flawed local model?

• Who’s liable if an intelligent product provides misleading advice?

• How are firmware updates, patching, and model retraining managed?

Boards should ensure product governance includes AI model testing, versioning, and explainability—even in edge environments.

3. Customer Trust and Regulatory Exposure Will Increase

Smart products behave more like agents than objects. They talk, remember, recommend, and infer. This changes the relationship between company and customer. If those interactions are mishandled—especially in sectors like healthcare, automotive, or financial services—the reputational damage could be significant.

Regulators are also beginning to focus on embedded AI, particularly in high-risk devices. Directors should ask:

• Do our compliance frameworks account for edge AI?

• Are we tracking emerging regulation on AI in consumer and industrial products?

• What customer disclosures or user agreements are in place?

Boards must ensure oversight structures are evolving in tandem with product intelligence.

4. AI as a Board-Level Skillset, Not Just a Management Issue

As LLMs move out of the lab and into products, the board’s role expands from oversight of back-office transformation to front-line innovation. Directors can’t afford to think of AI as purely a data science or IT issue.

A board fluent in embedded intelligence will:

• Better assess strategic bets.

• Ask sharper questions about product-market fit.

• Recognize the difference between innovation and gimmickry.

Final Thought: Intelligence Changes Everything

Embedded AI is not just an innovation—it’s a shift in how products behave, how customers interact with them, and how companies are judged. For boards, it represents both an opportunity and an obligation.

Products are getting smarter. Board oversight must get smarter too.