10 things companies should consider when building an AI strategy

Putting an AI strategy in place has never mattered more. These are ten steps to consider when deciding how to start:

• Align AI with business goals: decide how AI supports the strategy, whether that is lower cost, a better customer experience, or higher productivity.

• Data quality and availability: AI systems learn from data. Assess whether the data is available, relevant, and trustworthy, and how privacy and security are handled.

• Skills and talent: AI work needs specific skills. Look at the current team, the training on offer, and where new specialists may be needed.

• Ethics and regulation: consider privacy, bias, and transparency, and check that the strategy fits local and international rules.

• Infrastructure readiness: check whether current hardware, software, network, storage, and data systems can support the work.

• Vendors and partners: when working with an outside AI provider, set criteria for technical ability, track record, compliance, and flexibility.

• Change management: AI changes how people work. Plan communication, training, and support so teams can adopt it.

• Success measures: define clear KPIs, such as operational efficiency, sales, or customer satisfaction.

• Scalability: design the approach so it can handle more data and harder tasks as the company grows.

• Risk management: identify security gaps, system failures, and customer impact, and plan how each will be handled.