B4 AI Ecosystem Roundtable | 24 September 2026
Marnie Wills | Business With AI Strategist
Lead smarter. Stay human.
Round the table, 90 seconds each

Give a goal, no need for step by step guidance
Where is your data? Is it in the cloud?
Connect your softwares so AI fetches what it needs.
A traditional chatbot is mainly designed around conversation. You give it a prompt, and it generates a response.
An AI agent can go a step further by reasoning about a goal, planning what needs to happen, using external tools, taking actions, observing the results, and continuing the task based on what it finds.
Think of it this way: a chatbot is mostly question → answer, while an AI agent can work more like goal → plan → action → result → adjustment → completion.

Therefore: AI agents are software agents that use artificial intelligence to make decisions and take actions to complete specific goals. They interact with digital environments like emails, CRMs, and calendars, and analyse your inputs and respond accordingly.
Knows your business, voice and clients.
Knows the task, the rules and what good looks like.
Can reach your email, calendar, files and apps.
Follows steps to a goal, not just one answer.


*LLM's are my first recommendation ….followed by other Agent Building platforms
Give access to only what this task needs, read-only where possible.
Before anything is sent, posted, paid or deleted.
Keep client and confidential data out of tools you haven't vetted. Check where data is stored and whether it trains models.
Not personal ones. Know which agents are running.
Know what the agent did, and know how to switch it off.
Emails, web pages and documents can all carry hidden instructions.
A connector isn't handing over your password. You sign in on the app's own login page and approve specific permissions. You get a permission token, not your password shared. Revoke it any time by disconnecting in the app or in the third-party app's security settings.
On Team and Enterprise plans, users connect individually — the AI can only access tools and data that person already has access to. If someone can't see payroll in Xero, their AI can't either.
Enabling a connector for the organisation doesn't grant everyone access. Each person still authenticates individually. Owners can also disable specific tools that take write actions — allow "read" and block "send, edit, delete".
Every call the connector makes is logged — showing time, user, action and resource. The connector needs a business account; personal accounts can't be used. (Microsoft 365 example.)
Your AI Agent should be doing all of these Productivity, business efficiency and money generating
How can you add more memory quickly if needed?
What software's can you connect & why?
'What repeatable prompts or processes have you been using in your conversational AI that you could transfer to a skill? (top tip ask your AI)

Set a task once, and it runs on a schedule - a weekly briefing, a Monday priorities summary, a daily inbox triage.
Work that is repetitive, predictable and low risk.
Always design the approval checkpoint: what gets drafted for you, and what is allowed to send itself?
Most leaders measure AI on speed. The real return is capacity, quality, re-skilling, assets, monetisation
What is your teams capacity if they have access to agents?
Does the output waulity of the human improve
Whose role is shifting, and how are you supporting that?
What IP is being created, repurposed and what is the value of this?
Connectors given far more than the task needs.
Hidden instructions in an email, webpage or document that hijack your agent.
Confidential client or company data going to the wrong tool, account or model.
Sending, paying, publishing or deleting without a human check.
Staff using unapproved tools and personal accounts, so nobody sees the risk.
Who in your organisation owns AI risk today?
Have you seen, or nearly had, an AI mistake or data slip? What happened?
What would you need in place — policy, training, approved tools — to feel safe giving AI more access?
What does your client contract or UK GDPR obligation mean for how you use AI?

Clients now walk into meetings with AI-generated research, questions and expectations.
How is this changing the conversations you have with clients and customers?
Where does it help you, and where does it challenge your expertise or pricing?
What is your response: how do you add the value AI can't — judgement, trust, relationships?
Complete these three sentences and share one aloud:
By [date], my agent or workflow [name] will be running [how often].
The task it takes off my plate is ______.
The safety rule I'll put in place is ______.
I'll know it's working when ______.
AI Ecosystem Roundtable: 3 December 2026 at B4.
Next-Level AI: From Conversations to Agents That Act