Guide · 14 min read

What to automate first with AI: ten B2B workflows

The best first AI automation is rarely the biggest idea in the room. It is frequent, clearly owned work that wastes obvious time and can improve while judgement stays with a person. Here are ten workflows to assess, ranked, and a simple way to score your own.

How should you choose the first workflow to automate?

Choose frequent, clearly owned work with an output a person can check. The ranking below favours workflows that save visible time while judgement stays human.

The first AI automation in a business has two jobs. It has to save real time, and it has to earn enough trust that the second project is easier to approve. That rules out most of the ambitious ideas and points towards everyday work that is repetitive, well understood and easy to review.

Each workflow below is ranked on how often it happens, how visible the time saving is, how easy the output is to check and how little judgement it asks the software to make. Each one says what the workflow does and where a person stays in control.

This matches the advice Anthropic gives engineers in Building effective agents: find the simplest solution that works and add complexity only when it is needed. Most first projects are defined workflows rather than autonomous agents. If that distinction is new, the Bowtie Academy lesson on agents, chatbots and automations explains it in plain English.

1. Enquiry qualification and routing

An AI workflow can check each new enquiry against agreed rules, gather context from your CRM and route it to the right owner with a summary.

Inbound enquiries often arrive with too little context. Someone checks the company, searches the CRM for past contact, decides who should respond and hopes nothing is missed while they do it.

What the workflow does

• Looks up the sender and company in your CRM and approved public sources.
• Checks the enquiry against qualification rules your team has written down.
• Routes it to the right person with a short summary and logs what happened.

Where a person stays in control

• Any reply that goes to the customer.
• Enquiries that fall outside the expected pattern, or where the rules are unclear.
• Changes to the qualification rules themselves.

It ranks first because it happens every day, the output is easy to check and a slow or misrouted enquiry has a direct commercial cost.

2. Account and prospect research

A workflow can gather approved public and CRM information about an account and prepare a short, sourced brief before a meeting or outreach task.

Research is a strong early use case because it is repetitive, time consuming and easy for a person to review. The same questions come up before every first call: what the company does, what has changed recently, who is involved and what you already know.

What the workflow does

• Pulls recent activity and notes from your CRM.
• Gathers information from approved public sources, such as the company website and its announcements.
• Prepares a one-page brief in a consistent format, with links back to its sources.

Where a person stays in control

• Deciding which accounts deserve attention.
• Checking anything that will be repeated to a customer.
• Which sources the workflow is allowed to use.

The brief is a starting point for judgement. If a claim in it cannot be traced to a source, it should not be in the brief.

3. CRM data hygiene

AI can flag missing, duplicated or stale CRM records and prepare suggested fixes, so owners confirm changes instead of hunting for problems.

Most CRMs decay slowly. Contact details go stale, duplicates appear, owners change and deal stages stop reflecting reality. Every report built on top becomes a little less trustworthy.

What the workflow does

• Checks records for missing fields, duplicates and conflicting values.
• Prepares suggested updates with the evidence for each one.
• Asks the record owner to confirm or reject the change.

Where a person stays in control

• Merges, deletions and changes to critical fields such as deal value, stage and close date.
• The definition of a complete, healthy record.

Start with recommendations and an audit trail before granting any automatic write access. Our post on why CRMs become graveyards covers the causes, and governed action and provenance explains why every change needs a recorded reason.

4. Sales follow-up preparation

A workflow can assemble recent emails, meetings and CRM activity into a briefing and draft a next step for the salesperson to review.

Good follow-up depends on remembering what was said, what was promised and what happens next. That context is usually scattered across the inbox, the calendar, call notes and the CRM.

What the workflow does

• Gathers the recent conversation history for a deal or account.
• Summarises open questions, commitments and agreed next steps.
• Drafts a follow-up message or task for the owner to edit.

Where a person stays in control

• What is sent, to whom and when.
• Tone, pricing and any commitment made to the customer.

This reduces administration while the relationship stays with the person who owns it.

5. Weekly reporting and business summaries

If someone rebuilds the same numbers every week, a workflow can collect agreed metrics, highlight changes and prepare a draft for review.

Many teams spend part of every week copying numbers from several systems into a spreadsheet or slide, then writing the same kind of commentary around them.

What the workflow does

• Collects agreed metrics from each source system on a schedule.
• Highlights movements against the previous period and flags missing data.
• Prepares a structured draft summary with links to the underlying records.

Where a person stays in control

• Interpreting why a number moved.
• Anything that goes to a board, investor or customer.
• Which metric definitions count as the source of truth.

Reporting is often the easiest place to show time saved, because the before and after are visible. When a report is used daily, an internal app can be a better home for it than another email.

6. Sales-to-customer handover and onboarding preparation

A workflow can turn a closed deal into a structured handover, an onboarding checklist and first tasks, so customers repeat themselves less.

The move from sales to delivery or customer success is where context most often gets lost. The salesperson knows what was promised, the delivery team has to rediscover it, and the customer repeats information they already gave.

What the workflow does

• Assembles the customer record, agreed scope, stakeholders, goals and known risks.
• Creates an onboarding checklist and the first internal tasks, each with an owner.
• Flags missing information before the first onboarding conversation.

Where a person stays in control

• Scope, commercial commitments and delivery decisions.
• Customer-facing communication.
• Any judgement about risk or priority.

7. Meeting notes and action capture

A workflow can turn approved meeting transcripts or notes into a summary, decisions and owned actions, then prepare updates for your systems.

Meeting notes only matter if they turn into action. Decisions made on a call are easy to lose when nobody has time to write them up and update the CRM or project tool afterwards.

What the workflow does

• Summarises the meeting from an approved transcript or notes.
• Extracts decisions, actions and owners.
• Prepares updates for the CRM or project system, ready to confirm.

Where a person stays in control

• Whether a meeting is recorded at all, and making sure attendees know.
• Confirming that the summary reflects what was actually agreed.
• Anything sensitive that should not be stored.

Recording and transcribing people has data protection implications. For UK teams, the ICO guidance on AI and data protection is the right starting point.

8. Customer health and renewal signals

A workflow can watch agreed signals such as usage, support activity and engagement, then send the account owner a summary early.

Customer teams often learn an account is at risk after the renewal conversation has already started. The signals were there earlier, spread across product data, the helpdesk and the CRM.

What the workflow does

• Monitors the signals your team already trusts.
• Prepares a short account summary when a signal changes.
• Creates a follow-up task for the account owner.

Where a person stays in control

• The definition of a healthy account.
• Every conversation with the customer.
• Decisions about discounts, escalation or changes to the service.

It ranks below the workflows above because it depends on reliable data from several systems. If those definitions are not agreed yet, settle them first. Our post on what a revenue signal actually is covers how to choose them.

9. Internal knowledge retrieval

A focused internal assistant can answer questions from approved documents and records, with a link to each source, so people spend less time searching.

Teams lose time looking for the latest process, product note, policy or customer answer, or waiting for the one colleague who knows.

What the workflow does

• Answers questions from approved, access-controlled sources.
• Shows the source behind every answer so it can be checked.
• Records the questions it could not answer, which shows where documentation is missing.

Where a person stays in control

• Which sources are included, and who can see what.
• Keeping the underlying documentation current.

An assistant can only be as good as the information behind it, so the documentation work usually comes first, which is why it ranks ninth. This is often best built as an internal app with a defined job rather than a general chatbot.

10. Document and first-draft preparation

AI can prepare first drafts of account plans, briefs, summaries and internal updates from trusted source material, for a person to edit and approve.

Plenty of documents follow a known format and draw on information that already exists: account plans, meeting briefs, campaign summaries, launch checklists and internal updates.

What the workflow does

• Builds a first draft in an agreed template from named sources.
• Marks where information was missing or uncertain.

Where a person stays in control

• Editing, approving and owning the final document.
• Original judgement, positioning and anything high stakes.

It ranks last because the value depends heavily on editing discipline. Without a careful editor, fast drafts become fast mistakes. For marketing content, see using AI to write without destroying your brand.

How do you score a workflow before you build it?

Score each candidate on six questions: frequency, time cost, clarity, data readiness, risk and measurement. Workflows that score well on all six make strong first projects.

Use the ten workflows above as prompts, then score your own candidates. A simple rating of low, medium or high for each question is enough.

1. Frequency. Does the task happen often enough to justify improving it?
2. Time cost. Is a capable person spending too long on preparation, copying or chasing?
3. Clarity. Can you describe the current steps, the owner, the inputs and the expected output?
4. Data readiness. Are the systems and records accessible, reliable and properly permissioned?
5. Risk. Can important decisions stay with a person while the workflow handles preparation or routine steps?
6. Measurement. Can you compare time, quality, speed or error rate before and after launch?

A workflow that scores well on all six is a strong first project. One that scores low on clarity or data readiness usually needs process or data work before any automation.

What should you not automate first?

Avoid unclear, high-risk or unowned work as a first project. Broad agents, unapproved customer messages and processes built on poor data make weak starting points.

• A broad autonomous agent with access to every system.
• A customer-facing workflow with no approval step.
• A process nobody currently owns.
• Work that depends on poor data, with no agreed system of record.
• A workflow where success cannot be measured.
• A decision your team has not yet defined clearly enough to explain to a new colleague.

The safest first projects handle preparation, context gathering, routing or reporting, where a mistake is visible and easy to correct. The UK Government takes a similar line for public bodies: its AI Playbook asks teams to keep meaningful human control at the right stages.

We go deeper in which workflows you should not automate with AI, and what you should never hand an agent sets out the reversibility test we use. For guardrails on more autonomous systems, see the Agentic Revenue Field Manual.

What is a practical first step?

Choose one workflow, name its owner, collect three recent examples, map the tools involved and write down what good looks like before you build.

You do not need an AI strategy document to start. You need one well understood piece of work.

1. Choose one workflow from your scored list.
2. Name the person who owns it today.
3. Collect three recent real examples, including one that went wrong.
4. List every system and data source it touches.
5. Write down the baseline: how long it takes, how often it happens and what errors occur.
6. Agree which steps must stay with a person.

If you can do that, you are ready to assess the build. Our engagements follow the same shape: assess and plan, build and connect, then embed and improve. When you are deciding who should build it, our comparison of an AI automation agency and an in-house team sets out the trade-offs.

If you would like a second view, find your starting point with a short five-question brief, or read how we approach AI automation.

Frequently asked questions

What is the easiest process to automate with AI?

The easiest starting point is usually a frequent, repetitive task with clear inputs and an output a person can check. Common examples in B2B teams are account research, CRM data hygiene, meeting action capture, weekly reporting and enquiry routing.

Should we automate sales outreach with AI?

AI can research accounts, prepare context and draft outreach for a salesperson to review. Decisions about the message, the audience, the timing and the relationship should stay with a person, so start with preparation and human approval rather than automatic sending.

How do we measure the return on an AI automation?

Record a baseline before launch. Depending on the workflow, track time spent, response speed, completion rate, data quality, error rate or conversion. Treat projected savings as estimates until the new process has been used consistently for a full review period.

Do we need an AI agent or a simpler automation?

Use a rules-based automation when the steps are predictable. Consider an AI agent only when the work involves interpreting unstructured information or choosing between next actions within tight guardrails. Most first projects are better served by a defined workflow.

Who should own an AI automation after launch?

The person or team who owns the underlying work should own the workflow, including monitoring, exceptions and approving changes. A partner can build and support it, but ownership, access and documentation should be agreed before work starts.