Thinking Differently: How AI Can Help Businesses Solve Problems
Every business faces problems. A product may not be selling as expected, customers might be waiting too long for a response, costs can rise without warning or a team may struggle to find a fresh idea. Some challenges are small and routine; others can shape the future of the entire organisation. Whatever their size, solving them takes curiosity, information and the ability to look at a situation from more than one angle.
Artificial intelligence (AI) is giving businesses another way to approach these challenges. It can analyse information, identify patterns, generate possible explanations and help teams explore options they may not have considered. Used well, it can make problem-solving faster and more informed.
But AI is not a magic answer machine. It does not automatically understand a business, its customers or the consequences of every decision. The real opportunity comes from combining the speed and analytical power of AI with human experience, creativity and judgement.
This shift is already visible across the UK. The UK Government’s 2026 AI adoption survey found that 32% of businesses were using at least one AI technology in 2026, compared with 16% in 2025. Among businesses using or planning to use AI, improving efficiency and productivity was the most commonly reported driver. The figures show growing interest, but they also underline the importance of choosing practical uses that solve real problems.
1. Seeing a problem from a different angle
When a problem appears, it is easy to focus on the most obvious explanation. If sales fall, a business might immediately assume its prices are too high. If website visitors leave without buying, the team might decide it needs a redesign. Those explanations could be right—but there may be other factors worth exploring.
AI can help widen the investigation. A team can use it to organise customer feedback, compare sales patterns, summarise support conversations or suggest questions that challenge its first assumption. It might reveal that customers are confused by a particular product description, that delivery information is difficult to find or that enquiries tend to arrive when nobody is available to respond. For businesses exploring wider creative uses of AI, Can AI Unlock Creativity in Business? looks at how technology can help people develop ideas and approach familiar tasks in new ways.
The value is not that AI always finds the answer. It can help a team ask better questions before deciding what to do.
2. Finding patterns in information
Businesses collect information from many places: sales records, website analytics, customer reviews, stock systems, surveys and conversations with staff. When this information is spread across different tools, important signals can be difficult to spot.
With suitable, accurate and appropriately authorised data, AI can help summarise large amounts of information and highlight patterns for people to investigate. A retailer might look for products that are frequently bought together. A service company could examine the reasons customers contact support. A manufacturer might analyse equipment readings to help identify signs that maintenance could be needed. The OECD’s work on AI and productivity provides wider context on how AI is influencing organisations, work and economic activity.
Any pattern needs checking. A correlation does not necessarily explain why something happened, and incomplete or biased data can lead to misleading conclusions. People who understand the business should validate what the analysis suggests.
3. Generating more possible solutions
A team can sometimes become stuck because it keeps returning to the same ideas. AI can act as a brainstorming partner by suggesting alternative approaches, listing advantages and disadvantages, or looking at a challenge from the perspective of a customer, supplier or employee.
For example, if a small business wants to improve customer retention, AI could help it explore options such as clearer onboarding, more useful follow-up messages, a simpler returns process or a loyalty programme. The team can then assess which ideas are realistic, affordable and appropriate for its customers.
AI can also support early-stage product thinking. It might help organise customer needs, compare possible features or turn rough concepts into questions to test. This connects with From Idea to Innovation: Using AI to Develop New Products, which explores how AI can contribute to the journey from an initial idea to a product concept.
The strongest approach is to ask AI for a range of options, not to accept its first suggestion. A human team should choose which ideas deserve further investigation.
4. Supporting quicker, more informed decisions
Many business decisions involve trade-offs. A company might need to choose between investing in marketing, hiring another employee or improving an existing service. Each option has potential benefits, costs and risks.
AI can help prepare for these decisions by summarising relevant information, comparing scenarios and identifying assumptions that need to be tested. It can help a manager turn a broad question into a structured analysis: What outcome are we trying to achieve? What information do we have? What could go wrong? What would success look like?
This can make discussions more focused, but it should not turn into automated decision-making without oversight. AI-generated figures and explanations need to be checked against reliable sources. High-impact decisions about people, finances, safety or legal obligations require appropriate expertise and accountability.
5. Helping small businesses make the most of limited resources
Smaller businesses often have to solve problems without the specialist teams or large budgets available to bigger organisations. The owner may be managing customer service, marketing, stock, finances and operations at the same time.
AI tools can provide practical support with tasks such as sorting enquiries, drafting standard responses, summarising documents, preparing checklists and analysing simple business information. This can free up time for work that needs personal attention, such as building customer relationships or improving a service.
The aim should not be to automate every interaction. Customers still value being heard, and unusual or sensitive issues need a thoughtful response. For more on balancing technology with people, read Human Skills and Artificial Intelligence: Why Businesses Need Both.
Used carefully, AI can help a small team become more organised and responsive without pretending that technology can replace every role.
6. Testing ideas before making big changes
A proposed solution can sound convincing in a meeting but perform very differently in the real world. Before investing significant time or money, businesses need ways to test whether an idea is likely to work.
AI can help design a small experiment, draft customer survey questions, map a process or outline possible outcomes. A business considering a new booking process, for example, could use AI to identify likely friction points and create a checklist for a limited trial.
The next step is to test the idea with real users or real operating data. Measure a clear outcome, such as fewer abandoned bookings, shorter response times or a reduction in errors. Compare the results with the original situation and be prepared to change direction if the evidence does not support the idea.
A small, well-designed test is often more useful than a confident prediction generated by a tool.
7. Understanding the risks and limitations
AI can produce answers that sound convincing but contain mistakes. It may overlook important context, reflect bias in its training data or generate recommendations that are unsuitable for a particular business. If the information supplied is poor, the output may be poor too.
Businesses should decide what information staff are allowed to enter into AI tools, especially when it includes personal, confidential or commercially sensitive details. They should also understand how data is handled, check intellectual-property considerations and keep a person accountable for important outputs. The NIST AI Risk Management Framework offers a useful structure for thinking about trustworthy AI, including the need to identify, assess and manage risks.
A sensible rule is to treat AI output as a proposal to review—not as verified fact or an instruction that must be followed. The higher the impact of a decision, the stronger the checks and human oversight should be.
8. How to start using AI for problem-solving
Businesses do not need a complicated AI strategy to begin learning. They can start with one well-defined challenge and a simple process:
Describe the problem clearly. Explain what is happening, who is affected and why it matters. Separate what is known from what is only assumed.
Gather relevant information. Use reliable, permissioned data and remove personal or confidential details unless the chosen tool is approved to process them.
Ask AI to explore, not decide. Request possible causes, alternative explanations, questions to investigate and several potential solutions.
Check the suggestions. Look for unsupported claims, missing context, bias, costs and practical barriers. Ask people closest to the issue what they think.
Test one manageable change. Choose a low-risk experiment with a clear measure of success and a defined review point.
Learn and improve. Compare the result with the starting point, keep what works and adjust or stop what does not.
Thinking differently starts with asking better questions
AI is changing business problem-solving by helping people explore information, spot patterns, generate possibilities and test ideas. It can give teams another perspective and help smaller organisations make better use of limited time and resources.
But successful problem-solving is about more than finding an answer quickly. It means understanding the real issue, considering the people affected, checking the evidence and taking responsibility for the outcome. AI can support each stage, but it cannot replace the experience and judgement that make a decision right for a particular business.
The businesses that benefit most will be those willing to think differently without switching off their critical thinking. They will use AI to open up possibilities, challenge assumptions and support better decisions—while keeping people firmly in control.
Because sometimes the biggest breakthrough does not come from working harder at the same problem. It comes from seeing the problem in a completely new way.
