Where AI pays off in a business is rarely obvious from the technology alone. This page groups practical AI use cases by business function, from quick wins to larger bets, so you can see what is realistic for your organisation. Every use case starts with a clear business problem, the data it needs and a way to measure success.
New to this? Read our guides on how to implement AI in your company, AI transformation strategy and the AI implementation roadmap.
Explore our use cases
Recommend prices inside margin guardrails and flag the deals that leak margin.
Read the use case Business intelligenceAI business intelligenceAsk questions in plain language, get validated answers from your data, and an action plan with an owner.
Read the use case SalesAI RFP responses and proposalsAnswer RFPs and write proposals faster, from your own approved material.
Read the use case SalesAI prospect and market researchSummarise what matters about target companies and prepare a relevant first conversation.
Read the use case SalesAI sales outreach and lead generationQualify leads, draft follow-ups and keep the CRM current, so sales spends its time with buyers.
Read the use caseAI for sales
Sales teams in corporate markets win on speed, relevance and quality of the offer. AI helps most in three places, starting with the daily pipeline work.
AI sales outreach and lead generation
Most sales time disappears into admin: updating records, chasing stalled deals, qualifying leads and writing follow-ups. AI lead generation and AI sales outreach tools take over the repetitive part, so your team spends its time talking to buyers. Platforms such as Sonta.ai, an agentic CRM, keep the pipeline current, route new leads, draft personalised follow-ups and flag deals that need attention. People stay in charge of what is sent and promised. See our partner platforms, or read more about AI sales outreach and lead generation.
Market and prospect research
Good outreach starts with understanding the prospect. AI can summarise public information about target companies, their priorities and recent news, and help you prepare a relevant first conversation. Use public sources, keep a person in the loop, and respect data protection rules. Read more: AI prospect and market research.
From RFP to a solid offer, fast
Responding to a tender is a race against the deadline. AI can help your team in the steps that take the most time, while people keep control of the content and the commitments. Read more: AI RFP response and proposal writing.
- Extract requirements, deadlines and evaluation criteria from the RFP documents
- Build a compliance matrix and flag gaps and risks early
- Draft answers from your own approved past responses and case material
- Check consistency across sections and prepare the offer pack for human review
AI for marketing
Marketing teams are asked to produce more with the same people, and tool overload can make workload worse, not better.
- Drafting and repurposing content with human review
- Campaign reporting and summaries
- Audience research and segmentation support
- Structured briefs and consistent brand voice
Read why AI can burn marketers out and how to avoid it in our article on AI and marketing burnout.
AI for customer service
Customers expect quick, accurate answers in their own language.
- Drafting replies for agents to review
- Summarising conversations and cases
- Triage and routing of incoming requests
- Knowledge assistants built on your own documents
Not sure whether you need an agent or a copilot? See AI agents versus AI copilots.
AI for finance
Finance teams spend time assembling numbers instead of explaining them.
- Faster reporting and variance explanations
- Document and invoice processing
- Anomaly detection in transactions
- Contract and policy review support
Start with one report your team already produces and measure the time saved.
Pricing and margin. AI can recommend prices by SKU, channel and customer tier inside margin guardrails, and flag deals that leak margin. Read the use case: AI dynamic pricing for FMCG distributors.
Business intelligence with an action plan
Dashboards show what happened. Leaders need to know what to do next. AI business intelligence lets people ask questions in plain language, get validated answers from company data, and turn the findings into prioritised actions with an owner and an expected impact.
- Ask questions of ERP, warehouse and transport data without writing queries
- Get answers you can trace back to the source data
- Turn each finding into an action, an owner and an expected impact
- Start with one high-impact use case before widening the scope
Platforms such as Beye.ai, a generative BI workspace, do this, and we set it up with you, from the first proof of value to training your team. Read more: AI business intelligence: from question to action plan.
AI for HR and people
People teams handle high volumes of questions and documents.
- Internal assistants that answer policy questions
- Onboarding and training support
- Recruitment screening support, always with human review
Learn how teams build confidence with AI in our approach to AI training and capability building.
AI for operations and supply chain
Operations depend on forecasts, plans and exceptions.
- Demand forecasting and inventory planning
- Document processing
- Quality checks and exception alerts
For retail and consumer goods, platforms such as Leafio.ai automate supply chain and retail execution. See our partners.
AI for procurement and contracts
Buying teams compare suppliers, read contracts and track spend.
- Contract review support
- Supplier comparison
- Spend analysis
Choosing AI vendors well is its own skill: use our AI vendor checklist.
AI for IT and knowledge management
Every team asks IT and colleagues the same questions again and again.
- Assistants that search internal documents
- Ticket triage
- Documentation drafting
Governance matters most here, because internal data is involved. See AI governance and compliance.
Government and public services
Citizen-facing services, case handling and data platforms. See our Government & Public Sector page, or browse all industries.
Learn by doing, not by watching
Many people looking at AI use cases are looking for training. We think training on its own is not enough. Courses teach concepts, but habits change when people use AI on their own work. In our Bravvo approach, teams learn the concepts, test them straight away on real use cases from their own business, and finish with a hackathon where they apply everything together. Teams tell us it creates a before and an after.
Read more about AI training and capability building and our Bravvo approach.
Not sure where to start?
Begin with an AI readiness assessment or a Use-Case Discovery Workshop. We help you pick the use cases that fit your data, your people and your goals, and leave the rest for later. Get in touch.