There is no single price, because "AI strategy" covers everything from a £20-a-month tool subscription to a multi-year platform build. The useful question is not "how much does AI cost?" but "what is the cheapest way to prove value here?" - and the answer is usually far less than businesses fear.
What drives the cost
- Scope - one task versus enterprise-wide deployment
- Build vs buy - off-the-shelf tools are cheap; custom models are not
- Data readiness - messy data is where budgets quietly disappear
- People - training, change management and oversight time
- Integration - connecting AI to existing systems and workflows
Tools are rarely the expensive part; data, integration and people usually are.
A realistic starting budget
Most businesses can run a meaningful first pilot for the price of a few software subscriptions and some staff time - hundreds, not hundreds of thousands. Scale-up costs come later, once value is proven. For the costs that surface after launch, see the hidden costs of AI implementation.
How to control spend
- Start with off-the-shelf tools before considering anything custom
- Prove value on one task before committing budget
- Budget for the human work - training and oversight - not just licences
- Track cost against time saved so you can defend the spend
The bottom line
AI strategy can start cheap and scale with evidence - the risk is overspending before you have proof, or underspending on the people who make it work. Building a costed, staged plan is a core skill in the Strategic Application of AI in Business course at London School of Business UK. Enquire today.