Artificial intelligence has become the most overused phrase in the technology marketplace. From customer service chatbots to predictive dashboards, there is scarcely a product that has not been labelled as ‘AI-powered’. For a Chief Product and Technology Officer, this trend presents both risk and opportunity. The risk lies in being swept along by the marketing tide, presenting features that are little more than automation dressed up as intelligence. The opportunity rests in delivering genuine value, underpinned by transparent use of AI, that enhances both product performance and market perception.
The challenge begins with definition. Many so-called AI features are in fact traditional data science or rules-based automation given a new name. To customers, however, the distinction is rarely clear. As a CPTO, the responsibility is to ensure that what is presented to the market is both technically accurate and demonstrably beneficial. This requires an internal discipline of asking the hard questions: is the machine genuinely learning from data, improving outcomes, or making predictions that a human would struggle to achieve unaided? If the answer is no, the AI label should not be applied.
Checking if it’s true
Spotting AI Washing
Not every claim of being ‘AI-powered’ stands up to scrutiny. Watch for the following warning signs:
- The feature is little more than automation or pre-set rules.
- There is no explanation of how the AI model works or what data it uses.
- Performance cannot be measured or compared against a non-AI baseline.
- Marketing materials emphasise the label more than the outcome.
If these apply, the product may be more about branding than intelligence.
Equally important is the ethical dimension. Boards and investors increasingly recognise that AI adoption comes with responsibilities around fairness, accountability and transparency. Deploying algorithms that reinforce bias, or whose workings cannot be explained, can do lasting reputational damage. A technology leader who embeds governance processes into product development – ensuring training data is representative, model outputs are monitored, and customers are informed of how decisions are made – sets their organisation apart in a crowded marketplace.
What should a board be asking?
Questions Boards Should Ask About AI Claims
When a leadership team says a product uses AI, directors should probe deeper. Useful questions include:
- What specific AI techniques are being used, and why were they chosen?
- How is the model trained, and is the data set representative?
- What governance is in place to ensure the AI remains fair and explainable?
- What measurable value has been delivered to customers or operations?
These questions cut through jargon and help boards distinguish between hype and genuine capability.
Value creation must also be measured beyond marketing claims. Does the AI capability genuinely improve customer outcomes? Does it reduce costs, accelerate processes, or create new insights that change decision making? These are the measures that matter to customers, investors and boards alike. It is not enough to sprinkle machine learning across an existing product set; true adoption means identifying where AI can enable outcomes that would otherwise be impossible or impractical.
This also touches on the strategic positioning of the company itself. In markets where every competitor claims AI credentials, the firms that stand out are those able to evidence responsible, transparent, and impactful use. A company that can clearly articulate why it chose a particular AI approach, how it safeguards its use, and what tangible benefits have resulted, will be more trusted by clients and valued more highly by investors.
As CPTOs, we carry the responsibility of both innovation and restraint. Innovation in bringing the best of AI into our products in ways that are measurable, meaningful, and ethically sound. Restraint in resisting the temptation to apply the AI badge where it is not deserved. Cutting through the noise means ensuring that our products earn their claims, and in doing so, building not just market share but long-term trust.