Agentic AI: The new co-worker in your B2B team?
AI has been quietly reshaping how we work. But a new flavour of it is now making waves, and headlines. It’s called agentic AI. And it’s not just something you ask for help, it’s something that gets on with the job. Some headlines suggest it is the robots taking over. We’ll let you decide. And that is exactly the point I want you to remember when you think about agentic AI.
What is agentic AI?
Agentic AI refers to AI systems made up of autonomous agents; software that perceives their environment, makes decisions, takes action and learns from the results. Unlike traditional AI that responds to a prompt, agentic AI is proactive. It can work through multi-step tasks, juggle tools and data sources, and improve over time. It is a whole new use case and one more akin to hiring an assistant.
Why it’s in the news now
Agentic AI hit a high in July 2025, when OpenAI announced ChatGPT Agent. It can browse the web, run code, navigate platforms and apps — all on its own virtual computer — to research, reason, and take real-time actions to complete entire workflows for you. So far, so good.
It contains fail-safes: pause, redirect, or stop its work at any time. The fact that this is part of the marketing shows how governance of AI is vital. We’ve made strides on this as an agency with our orchestration services to train, control, and correct AI models. It is the new frontier for B2B marketers: orchestrating AI.
What could agentic AI mean for B2B marketers?
So far, case studies are few and far between. There are some obvious places which would benefit from it. In terms of rolling out, our prediction is that agentic AI will start to appear in common martech platforms as enhancements. We know that the UK government wants to encourage AI adoption through established platforms. We know this for a fact as it was covered when I was consulted on UK policy.
Where could agentic AI make the biggest difference in B2B?
- ABM campaign development via ABM platforms like Demandbase or HubSpot
- ICP discovery and research: Agents can scan the market, social signals, firmographics and news to assemble target account insights.
- Automated journey orchestration: From segmentation to outreach, agents can create, trigger and adapt ABM plays with little input as criteria are reached.
- Content asset generation: Based on buyer stage, persona, or behaviour, agents can auto-generate tailored assets — email sequences, PDFs, even pitch decks.
- Sales enablement via platforms like SFDC
- Real-time account intelligence: AI agents can scan CRMs, emails, call logs and web activity to brief reps before meetings.
- Dynamic pitch support: Agents help draft messaging, structure proposals, and even pre-empt objections based on past win/loss data.
- Action prompts: Like a smart assistant, the agent can nudge reps to follow up at the right time, or log key activity automatically.
- Customer service & internal team support via brand platforms or Zendesk
- Customer query resolution: Agents can deflect, triage, and resolve tickets — learning from your knowledge base and past outcomes.
- Self-serve internal helpdesk: Team members can tap into agent support for policy queries, training materials or IT requests. Brand feedback could be automated.
- Lifecycle orchestration: Post-sale, agents can steer onboarding, engagement and renewal workflows — keeping human touch where it matters most.
Where is this already happening?
IBM has been leading the charge with watsonx Orchestrate, a platform built around AI agents for enterprise use. Their tools include pre-built agents for sales, HR, procurement and support, plus an agent builder for creating task-specific workflows yourself. Most interestingly, an Orchestrator Agent that manages sub-agents to execute complex tasks like lead engagement or content creation — AI governing itself to set rules.
Similarly, Adobe’s Experience Platform Agent Orchestrator blends agentic AI into marketing tools like Marketo and Journey Optimiser. It’s already helping B2B marketers discover buying groups, build journeys, generate content and feed actionable insights to sales teams. Very much about enhancing what is already there.
With such size comes a vital need for governance.
To integrate your MarTech or not integrate — that is the question
These enhancements are starting to appear in the larger MarTech platforms that have the benefit of scale. For those B2B marketers targeting a niche audience using a combination of tools brought together, this may be a while off.
I’m old enough to have worked in email marketing since its inception and can remember many situations where brands automated email journeys to go beyond personalisation, but inadvertently produced upsetting communications. Father’s Day alerts for those who have lost family members are why you now see emails offering to unsubscribe you from those emails. It is the same for brands around childbirth, and having started my career working on the Mothercare account, I know only too well how getting this right is important. Controlling automation and AI is vital.
So what should you do next?
Wait until they appear in the platforms you use most. You could build your own, but the speed of AI means you won’t need to wait long. We’re recommending waiting — but use the time to plan what guardrails would be important. Form a plan before you need a plan.
Agentic AI is no longer theoretical. It’s already working in enterprise B2B environments. As with all tech shifts, those who experiment early — but with their eyes wide open — will squeeze out most of the benefits. This isn’t just automation. It’s augmentation. And it will come through the tools you already use. Now is the time to start thinking about governance if you haven’t already.
