AI Strategy: A Guide to AI Strategy for Businesses
A practical guide to using AI to achieve your business goals.
AI strategy is about deciding where AI can create value for your business, which opportunities to prioritise and what capabilities you need to turn those opportunities into results.
It is not simply about choosing AI tools. A good AI strategy connects AI investment to business priorities, identifies the right use cases and provides a practical path from opportunity to implementation.
What is AI strategy?
An AI strategy is a plan for how a business will use artificial intelligence to achieve specific business objectives.
It should answer some fundamental questions:
- Where could AI create the most value?
- Which problems should we solve first?
- What should we build, buy or integrate?
- What data and technology will we need?
- What skills and expertise are required?
- How much should we invest?
- How will we measure the results?
- How will we manage AI risk and governance?
Microsoft describes AI strategy as a coordinated plan that connects AI with organisational goals, while IBM describes it as a roadmap for integrating AI with broader business objectives.
Why do businesses need an AI strategy?
AI is developing quickly and businesses have access to more tools and capabilities than ever.
The challenge is deciding what is actually relevant to your organisation.
Without a clear strategy, businesses can end up experimenting with disconnected tools, running pilots that never reach production or investing in technology without a clear business outcome. Microsoft specifically identifies duplicated effort, stalled pilots and fragmented investment as risks of an ad-hoc approach.
An AI strategy provides a framework for deciding where to focus.
It starts with the business problem rather than the technology.
What should an AI strategy include?
There is no single AI strategy that works for every organisation. The right approach depends on the business, its objectives, data, technology, people and industry.
A comprehensive AI strategy will typically consider:
Business objectives
What is the business trying to achieve?
This might include increasing revenue, reducing costs, improving customer experience, increasing productivity, improving decision-making or developing new products and services.
AI opportunities
Where could AI make a measurable difference?
This could include automation, customer service, sales, marketing, finance, operations, software development, data analysis or product development.
Use-case prioritisation
Not every AI opportunity deserves investment.
Potential use cases can be assessed according to factors such as business value, feasibility, cost, risk, data availability and the time required to deliver results.
Microsoft's current AI strategy guidance similarly recommends starting with business problems and identifying use cases that can be connected to measurable value.
Data and technology
AI depends on the underlying technology and information available to the organisation.
An AI strategy may therefore need to consider data quality, data architecture, cloud platforms, existing applications, AI models, integrations and security.
People and skills
AI projects require the right combination of business and technical expertise.
Depending on the project, this could include:
- AI strategy consultants
- AI transformation consultants
- Data scientists
- Data engineers
- AI developers
- Machine learning specialists
- AI automation specialists
- AI product specialists
- AI governance specialists
Governance and risk
Businesses also need to consider how AI will be used responsibly.
This can include security, privacy, data protection, regulatory requirements, human oversight and internal AI policies.
Investment and ROI
An AI strategy should provide a basis for deciding where to invest and how success will be measured.
The objective is not to implement AI for its own sake. It is to connect investment to business outcomes.
AI strategy vs AI transformation
AI strategy and AI transformation are closely related but they are not the same thing.
AI strategy determines where AI should be used, why it matters and what the organisation needs to do.
AI transformation focuses on putting that strategy into practice and changing processes, teams, technology and ways of working.
A business might therefore start with an AI strategy, identify several high-value opportunities and then develop an AI transformation programme around them.
AI strategy vs AI consulting
AI strategy consulting is one way of developing an AI strategy.
An AI strategy consultant can help a business assess its current position, identify opportunities, prioritise use cases and develop a roadmap.
The expertise required will depend on the problem. Some businesses need strategic leadership. Others need technical specialists, data expertise, automation skills or experience in a particular industry.
When should a business develop an AI strategy?
An AI strategy can be useful when:
- You know AI is important but do not know where to start.
- Different teams are experimenting with AI independently.
- You have identified several AI opportunities but cannot prioritise them.
- You are considering significant AI investment.
- You want to automate business processes.
- You are developing an AI-enabled product or service.
- You need to understand what skills you are missing.
- You want to move from AI experiments to implementation.
- You need a roadmap for wider AI adoption.
You do not necessarily need a large enterprise-wide programme. For some businesses, the right starting point is a focused assessment of one business problem or opportunity.
What does an AI strategy consultant do?
An AI strategy consultant helps connect business objectives with practical opportunities to use AI.
Depending on the assignment, they may:
- Understand the organisation and its objectives
- Identify potential AI use cases
- Assess existing AI capabilities
- Analyse processes and opportunities for automation
- Evaluate data and technology requirements
- Prioritise opportunities
- Develop an AI roadmap
- Estimate investment and potential value
- Identify required skills and expertise
- Support implementation planning
- Help establish AI governance
The role sits between business strategy and AI capability. The right consultant needs to understand both the commercial problem and the technology available to solve it.
What AI expertise might you need?
AI strategy is often the starting point rather than the final requirement.
Once the opportunity is understood, a business may need other specialists.
For example:
The challenge is often not finding an AI consultant. It is finding the right type of AI expertise for the problem.
How to find the right AI expertise
Start with the business problem rather than the technology.
Describe what you are trying to achieve in your own words.
The right assessment can then help identify the type of AI expertise that may be relevant, explain why it fits the problem and point you towards the specialists who can help.
Frequently asked questions
- What is an AI strategy?
- An AI strategy is a plan for using artificial intelligence to achieve specific business objectives. It identifies opportunities, priorities, capabilities, investment and the steps required to put AI into practice.
- How do I create an AI strategy?
- Start with your business objectives and problems rather than individual AI tools. Identify where AI could create value, assess potential use cases, prioritise them and determine the data, technology, people, investment and governance required.
- Do small businesses need an AI strategy?
- A small business may not need a complex enterprise AI strategy. However, a clear view of where AI could create value can help prevent wasted investment and focus limited resources on useful opportunities.
- What is the difference between AI strategy and AI transformation?
- AI strategy establishes where and why AI should be used. AI transformation focuses on implementing those priorities and changing the processes, technology, people and ways of working required to achieve them.
- What does an AI strategy consultant do?
- An AI strategy consultant helps businesses identify AI opportunities, prioritise use cases and develop a practical roadmap aligned with business objectives.
- What skills are needed for an AI strategy?
- The skills required depend on the business and its objectives. They can include business strategy, AI expertise, data science, data engineering, software development, automation, product development, governance and commercialisation.
- How much does AI strategy consulting cost?
- The cost varies significantly depending on the size and complexity of the business, the scope of the work and the expertise required. A focused assessment will generally require less work than a comprehensive enterprise AI strategy.
- Where should a business start with AI?
- Start with a business problem or opportunity. Identify where better decisions, automation, productivity, customer experience, new products or revenue could create value, then determine whether AI is an appropriate solution.
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