AI in business is the use of artificial intelligence to help companies analyse information, automate tasks, support decisions and improve how work gets done. It can be applied to activities such as forecasting demand, identifying unusual transactions, summarising financial results, drafting customer communications and recommending next steps based on business data.
For growing companies, AI is becoming a practical layer of infrastructure because it can sit inside the systems employees already use for finance, sales, inventory, HR, customer service and reporting. Instead of treating AI as a separate piece of software, leaders can apply it to specific business questions, such as which customers are most likely to pay late, which products may need more stock next month or where teams are spending too much time on manual work.
AI adoption is rising among smaller and growing companies in the UK. British Chambers of Commerce research found that 35% of SMEs were actively using AI in 2025, up from 25% in 2024, while a further 24% planned to adopt it. That suggests AI is moving beyond enterprise experimentation and into the everyday operations of businesses with fewer resources and smaller teams.
AI in Business Explained
AI in business works by using data, algorithms and models to identify patterns, generate content, make predictions or recommend the next best action. Some AI tools classify information, such as tagging support cases by urgency, while others use machine learning to detect patterns in historical data.
Take AI in the retail sector, for example. AI-driven forecasting can help reduce food waste by aligning inventory levels with customer demand or using dynamic pricing to stay competitive in changing market conditions. In the manufacturing sector, AI can monitor equipment performance to predict when maintenance is needed, minimising high production disruption costs and reducing risks associated with unexpected equipment breakdowns.
Generative AI goes a step further, as it can create drafts, summaries and explanations based on prompts written in natural language. Agentic AI, a newer area of adoption, can plan and carry out multi-step workflows. The most valuable business outcomes come when AI is connected to trusted business data through workflows with clear approval steps and defined goals.
Why Is AI in Business Important?
AI in business is important because teams are being asked to make faster decisions and consider more data, while businesses experience tighter margins and higher customer expectations.
Leaders are also under pressure to improve productivity. Microsoft’s 2025 Work Trend Index found that 53% of leaders said productivity needs to increase, while 80% of the global workforce reported lacking the time or energy to do their job. The same report found that 82% of leaders expected to use “digital labour” to expand workforce capacity in the following 12 to 18 months.
AI can help finance teams review exceptions, sales teams focus on likely opportunities and operations teams anticipate changes in demand. It can also reduce repetitive work, freeing employees to spend more time on analysis, service and planning. AI is most useful when it is aimed at measurable business outcomes rather than broad experimentation.
Advantages of Using AI in Business
When used effectively, AI in business can help companies achieve a number of business goals and KPIs, including the following:
- Making faster decisions by summarising operational, financial and customer data for leaders and department heads.
- Improving forecast accuracy by identifying patterns in sales, inventory, cash flow and demand.
- Supporting accounting teams by helping review transactions, detect anomalies, prepare reconciliations and reduce manual work during the monthly close.
- Reducing manual effort in repetitive tasks such as document review, content drafting, invoice processing and data classification.
- Strengthening customer service by helping teams prioritise enquiries, prepare responses and surface relevant account information.
- Spotting risks earlier, including unusual spending, late payments, margin pressure or supply delays.
- Giving employees more time for higher-value work, such as analysis, planning, customer conversations and exception management.
How to Implement AI in Business
To use AI in business effectively, start with specific operational challenges, connect the right data and build in clear review steps before expanding to wider use:
- Start with a business problem, not a tool: Identify a recurring decision, bottleneck or manual task where better speed or accuracy would create clear value. Examples include cash flow forecasting, invoice exception handling, stock planning and customer support triage.
- Check whether the right data is available: AI depends on relevant, reliable data, so review where the data lives, who owns it and whether it is complete enough for the task. This is where integrated ERP systems can help. NetSuite customers already manage finance, CRM, ecommerce and operations data in one suite, giving AI more complete context for recommendations, summaries and analysis.
- Build review and approval into the process: AI outputs should be checked by the people responsible for the decision, especially in finance, legal, HR and customer communications. Clear review steps help teams benefit from AI without treating every output as final.
- Measure results against the original goal: Track whether AI reduces task time, improves forecast quality, raises service response rates or helps employees make better decisions. McKinsey’s 2025 research found that although 64% of respondents said AI was supporting innovation, only 39% reported an enterprise-level EBIT effect, which makes measurement especially important.
- Expand from proven use cases: Once a team has shown value in one process, apply the same governance, data checks and training to related workflows. This approach helps AI adoption grow in a controlled way.
How NetSuite Supports AI in Business
NetSuite embeds AI across its suite to help companies increase productivity, analyse data faster and generate deeper insights. NetSuite SuiteAnalytics provides business intelligence tools, including NetSuite Analytics Warehouse, workbooks, saved searches, reports and dashboards. NetSuite 2025.2 expanded AI-powered capabilities across the platform, including features that generate insights and summaries without requiring employees to build reports.
AI in business is most effective when it is connected to trusted data, focused on specific work and supported by human review. Recent adoption data shows that AI is now widely used, and many companies are taking early learning from isolated pilots and applying it more generally to create measurable business value. Companies that start with practical use cases such as forecasting, reporting, customer service and finance operations can turn AI into an essential business capability.
AI in Business FAQs
How is AI used in business intelligence?
AI benefits business intelligence by analysing large volumes of data, identifying patterns and generating insights faster than traditional methods. It helps organisations improve forecasting, reporting and decision-making through predictive analytics and automation.
What is the role of AI in business?
The role of AI in business is to improve efficiency, support decision-making and automate repetitive tasks. It helps organisations reduce costs, improve customer experiences and uncover new opportunities through data-driven insights.
How will AI transform the workplace?
AI will transform the workplace by automating routine activities, allowing employees to focus on more strategic and creative work. AI is also helping teams improve productivity, support better decision-making and create new ways of working across industries.
How is AI changing business?
AI is changing business by helping organisations process information more quickly, personalise customer experiences and make more informed decisions. It is also driving innovation across areas such as customer service, operations, marketing and supply chain management.
What is an example of an AI-driven business model?
An AI-driven business model uses artificial intelligence as a core part of delivering value to customers. For example, streaming platforms such as Netflix use AI to analyse viewing behaviour and provide personalised content recommendations that improve user engagement and retention.
