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Tech Transformed video podcast 26 min

Scaling AI Across the Enterprise: From Builders to Business Impact

Sara Maldon, Head of AI and Automation at Make, joins Christina Stathopoulos to explore automation, agentic AI and the workflows that actually scale across a business.

Guest Sara Maldon Head of AI and Automation at Make
Host Christina Stathopoulos Founder of Dare to Data

In this episode

  • When a workflow really needs an agentWhere deterministic automation is enough, and where autonomy earns its place.
  • Why agentic AI is about resilienceAgents adapt when a website, system or process changes instead of breaking overnight.
  • How to build a culture of buildersDomain knowledge beats coding skill when business teams automate their own work.
  • What scaling actually costsTwo days to build an agent, four weeks to map the pipeline, four months to drive adoption.
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About the episode

"We need agents" is a starting point, not a strategy

There is barely a strategy meeting today where someone does not say "we need agents." Sara Maldon, Head of AI and Automation at Make, has heard it countless times, and has learned to treat it as the beginning of a conversation rather than the answer. Most of the time, the business problem underneath does not need an agent at all.

This episode is less about hype and more about judgement: when a workflow needs autonomy, and when a simple if-this-then-that rule is already doing the job. Maldon draws on two and a half years of running AI transformation inside a company that was automating long before "agentic" became a buzzword.

Even Make's own AI sales agent, deployed across 60 sales representatives, is 95 per cent deterministic. The agent only steps in where a judgement call adds value.

What you will learn

A practical discussion for AI, automation and operations leaders

01

Where agentic AI fits on the automation spectrum

Deterministic pipelines still carry most of the work; agents add adaptability where environments change.

02

Why domain knowledge beats coding skill

Operations, customer success and marketing teams see where processes break, which makes them the best builders.

03

How to scale beyond the prototype

The hard part is not the AI. It is the mapping, training, feedback loops and adoption around it.

04

What a builder culture looks like

96 per cent of Make employees run an AI agent they built themselves, driven by low friction rather than mandates.

Inside the conversation

Five themes across the 26-minute episode

The discussion moves from deciding when to use agents, through building with AI, to scaling automation across an entire business.

  1. 01Why "we need agents" is rarely the real requirement
  2. 02Where agentic AI fits on the automation spectrum
  3. 03Building with AI when you are not a developer
  4. 04Scaling automation across teams and departments
  5. 05Patience, adoption and the soft skills of AI transformation

The executive takeaway

Stop assessing tools and pick one. The market moves faster than any evaluation process can keep up with.

Building the agent took two days. Mapping the deterministic pipeline around it took four weeks. Rolling it out to 60 people took four months. The lesson for leaders: start small, iterate quickly, and give people time to trust a new process.

In partnership with

Make is a leading visual platform for AI and automation, letting teams design, build and run workflows that connect the apps and systems they already use. From simple deterministic automations to agentic workflows, Make helps business users and technical teams automate work at scale without writing code.