Agentic GTM has a trust problem, and it is getting expensive. Gartner predicts more than 40 percent of agentic AI projects will be canceled by the end of 2027, citing escalating costs, unclear business value, and inadequate risk controls.  

The upside for teams that get agentic GTM right is just as large. B2B software teams with high AI adoption generate roughly twice the net new ARR per GTM employee of low adopters, according to ICONIQ: $640,000 versus $370,000.

Agentic GTM is a way of running go-to-market in which AI agents make decisions and act toward goals your team defines, within boundaries your team controls. Agents research accounts, prioritize them, and reach out. People set the strategy and the limits. It works whether you run lead-based, account-based, or opportunity-based GTM.

Four steps get you there. Each one ends with an action you can take this week.

Step 1: Check if your context is adequate

Everything else rests on context, so it comes first. Context is what your team and your agents know about each buying group: who is involved, what they are doing, and what it means. Good context has two traits:

  • Shared. Your team, your agents, and your vendors’ agents all work from the same picture. ‍
  • Explainable. Every recommendation shows what happened, why it matters, the evidence behind it, and how sure the system is.

Here is why that matters. Picture a customer in the middle of a renewal who visits your pricing page. Three agents see the same visit:

  • Agent one has no account context and pitches a product the customer already owns. Awkward.
  • Agent two checks the CRM, sees the open renewal, and stays quiet. Sometimes the best action is no action.
  • Agent three sees the renewal and 30 days of searches about an adjacent module, then sends a short note with a relevant case study. It also identifies the 12 people in the buying group and tailors a message to each role.

Reaching more of the buying group pays off. 6sense data shows that teams engaging 11 or more members of a buying group convert at about 19 percent, while teams engaging a single contact convert at under 5 percent.

Exercise: Is your context adequate?

Pick one account and ask your rep, your agent, and one vendor’s agent to describe it. If the answers differ, or none of them can say why the account matters, you have found your first context gap.

Step 2: Align on strategy and outcomes

Agents work fast and never get tired. When new data arrives and no human is there to make the call, the agent makes an assumption and moves on. The fix is specificity. For each segment, answer four questions:

  • Who do you target?
  • What do you pitch?
  • Based on which trigger?
  • Who sells?

Then give the agent the metrics the play has to hit. Over time, your agent compares your answers to results and recommends adjustments. You work with your agent to improve strategy.

Exercise: Decide metrics  

Pick one segment. Answer the four questions in one sentence each and name the metric that tells you the play is working.

Step 3: Architect your tools and agents

Decide what to build, what to buy, and what you already own. A useful rule of thumb: Buy when a vendor meets more than 80 percent of your needs and build only where you need something that sets you apart. Avoid tying the whole setup to one vendor.  

The strongest setups combine your agents, vendor agents, fixed rule-based workflows, and the right moments for a person to review.

Then set the level of autonomy for each workflow:

  • Suggest. The agent recommends, and you decide. ‍
  • Approve. The agent prepares the action, and you sign off before it goes out. ‍
  • Act. The agent acts on its own within limits you set. For example, it sends only when it is more than 90 percent confident in both the action and the message. Otherwise, it asks a person. People set that confidence line. The agent does not.

Exercise: Test and advance autonomy levels  

Choose one workflow with a clear trigger, such as the pricing page visit from the renewal example. Begin with the agent recommending the next move. Only let it act once its decisions prove consistently right, including pausing for human review when something is ambiguous.

Before you start, pick two kinds of metrics:

The outcome metric from Step 2. For this workflow, that could be reply rate on notes sent by an agent, meetings booked from the visit, or the renewal rate for accounts that received notes.

A guardrail metric, such as unsubscribes, complaints, or messages a person had to pull back because the recommended note missed the mark.

Give the agent more autonomy when the outcome metric holds and the guardrail stays clean. If the guardrail slips, return to sign-off before sending and review what the agent did, what your team approved, and what they overrode.

Step 4: Empower your people

Your people need three things to lead agents well: a clear strategy, easy access to the same context your agents use, and control over what agents do. Three controls make that last one real:

  • Log every action, so anyone can see what an agent did and why. ‍
  • Make actions reversible where you can, such as pausing a sequence, removing an account from an audience, or reverting a field update. ‍
  • Require approval before an agent acts, for any workflow you choose.

With those in place, your team can say yes to agents faster, and the work divides cleanly. Agents handle research, prioritization, and outreach. People handle decisions, judgment, and relationships.

The renewal example shows the split. After the agent warms up the buying group, it briefs the CSM. The CSM calls the next morning. The agent opens the door, and the human wins the deal.

Teach your team to manage agents — and start with managers. When managers use AI visibly in their own work, their teams report more value from it and more trust in agents.

Exercise: Share what you learned  

Ask one manager to walk the team through a real agent workflow they use, including what the agent did, what they approved, and what they overrode.

Start with one workflow, then expand

Start with one workflow

Pick one workflow, run it through all four steps, and prove the results before you add the next. Teams that earn trust this way can expand with confidence, because each workflow rests on context people can check.

How 6sense helps

  • Context: Contextual Intelligence pairs 6sense data with your own to explain why an account matters, why now, and what to do next, with the evidence behind each recommendation. APIs and the 6sense MCP server carry that context into your own tools and agents. ‍
  • Flexible deployment: Run Contextual Intelligence in 6sense with Advertising, the Email agent, Sales Intelligence, and RevvyAI, or build it into your own stack. The intelligence is the same either way. ‍
  • Learning: The Agentic GTM Certification teaches your team how to put agentic GTM into practice.

Earn your Agentic GTM Certification

The Agentic GTM Certification is a free online course that teaches you how to put agentic GTM into practice with your own team. Sign up, and bring along the colleagues who will run these workflows with you. Questions along the way? Ask the community at RevCity (free to register) or book a demo to get the 6sense team on the line.

Good luck! If you have any questions, you can use our community forums at RevCity (free to register) to ask questions or book a demo to get us on the line.  

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