How to Identify AI Opportunities in Your Business

AI opportunities are best identified by examining business problems and processes rather than starting with AI tools.

Look for areas where meaningful manual effort, delays, errors, capacity constraints or poor customer experiences exist. Then assess whether technology could improve the underlying process.

AI should be considered as one possible approach—not automatically selected as the answer.

A useful opportunity assessment starts by asking what the business wants to improve.

The problem might involve cost, capacity, customer response, employee productivity, information access, lead handling or the quality of a digital experience.

Once the problem is understood, examine the process behind it.

• What starts the process?
• What steps happen?
• Who performs each step?
• What systems and information are involved?
• How frequently does the process occur?
• Where does manual effort accumulate?
• Where do delays, errors or exceptions occur?

Friction is often where useful opportunities become visible.

A process may involve repetitive data entry, copying information between systems, responding to similar enquiries, searching for information, manually reviewing documents or coordinating work across several people.

The presence of friction does not automatically mean AI is the answer. It indicates that the process may be worth investigating.

The next question is whether AI genuinely adds value compared with simpler alternatives.

AI can be particularly useful where work involves unstructured language, classification, interpretation, summarisation, generation or interaction with people.

Where the process is completely predictable and rule-based, traditional automation may be simpler, more reliable and more appropriate.

A promising opportunity should then be considered from three perspectives: potential business value, feasibility and risk.

• Potential value to the business
• Implementation complexity
• Data and system readiness
• Security and privacy considerations
• Process exceptions
• Human judgement requirements
• Reliability and control requirements

Businesses will often identify several potential opportunities. They should not all be treated equally.

Prioritisation should consider value, strategic relevance, feasibility, readiness, risk, complexity and expected time to value.

The result should be a clearer view of where deeper discovery is worthwhile.

The broader DEEPS framework moves from the business problem through process understanding, friction, frequency, manual effort, data and systems, exceptions and AI suitability before arriving at the opportunity decision.

The DEEPS AI Opportunity Finder is designed to provide an initial signal based on a small amount of business information.

Its purpose is to help identify potential areas worth exploring. The information collected at this stage is not intended to replace detailed discovery or consulting judgement.

A more thorough discussion is required to understand the actual process, constraints, systems, risks and business objectives before a recommendation can be made.