ON DEMAND • Podcast Episode

From Sales to AI Agents: The New GTM Playbook

AJ Cook from Workato joins Better Tech to discuss how integration, automation, GenAI, and AI agents are changing go-to-market workflows, from CRM updates and meeting prep to CPQ automation and sales research.

FEATURED GUEST

AJ Cook

Our featured guest

AJ Cook

Workato

AJ Cook brings a practical view on Agentic AI, automation, and workflow design. In this episode, he explains why not every AI use case needs an agent, and why teams should choose the most reliable tool for each workflow.

He also covers:

  • Why integration and automation are becoming the foundation for Agentic AI
  • When to use workflow automation vs AI agents
  • How to avoid model and vendor lock-in
  • Why governance, access control, and observability still matter
  • How AI can reduce GTM admin work and increase revenue-generating time

Why this conversation matters now

Growing businesses are under pressure to move fast on AI, but many teams are still unclear on where automation ends and agents begin.
This episode explores the questions leaders are asking now:

01.

Which workflows should be automated, and which actually need AI?

02.

When does an AI agent make sense?

03.

How do we avoid locking our architecture into one model or vendor?

04.

What governance controls are needed before AI touches business data?

05.

How can AI reduce GTM admin work without replacing human judgment?

06.

How do we prove ROI before scaling AI across teams?

What you'll learn in this episode

01.

Why integration and automation are prerequisites for scalable AI workflows

02.

How to compare deterministic automation, LLM-assisted workflows, and agentic processes

03.

Why the most deterministic tool is often safest for business-critical workflows

04.

How model lock-in can create long-term architecture risk

05.

Why logging, observability, access control, and entitlements cannot be skipped

06.

How pre-built AI applications can help teams overcome analysis paralysis

07.

Where AI is already reducing sales and GTM admin work

Who this episode is for

CTOs and CIOs CEOs and business leaders Revenue and GTM leaders Operations leaders Digital transformation teams Mid-market companies exploring AI agents

Our host

JocelynHoule

Jocelyn Byrne Houle

AI and data product leader

Jocelyn Byrne Houle is an AI and data product leader, entrepreneur, and investor who has built and scaled transformative technology initiatives across finance, cloud governance, and AI security. She founded Deploy Forward AI to help enterprises adopt AI with strong governance, operational discipline, and long-term organizational ownership.

A preview of the key takeaways

01.

Agentic AI starts with connected systems

Before AI agents can act across a business, they need access to the right systems, data, and workflows. AJ explains why integration and automation form the foundation for more advanced AI use cases.

02.

Not every workflow needs an AI agent

Some use cases are better solved with predictable, rule-based automation. The goal is not to use the most advanced tool. It is to use the most reliable one for the job.

03.

Flexibility matters more than betting on one model

The AI market is changing quickly. Building everything around one foundation model can limit optionality if a better, cheaper, or more relevant model emerges later.

04.

Governance is not optional

AI workflows need the same controls as human users, including logging, observability, role-based access, and entitlement management.

05.

AI will reshape GTM work at the task level

AI can support repetitive GTM tasks like CRM updates, meeting summaries, company research, CPQ support, and account preparation, giving teams more time for revenue-generating work.

Why tkxel is hosting this conversation 

 tkxel helps growing businesses move AI from pilots into real workflows through strategy, data integration, product engineering, and responsible implementation.
This episode reflects a challenge many teams face today: AI agents sound promising, but value depends on connected systems, workflow clarity, governance, and practical use case selection. AJ’s perspective adds context for leaders deciding where to use automation, where to use AI, and how to scale adoption without creating unnecessary risk.

WHERE TKXEL BRINGS CONTEXT

1 AI strategy and adoption 2 Workflow automation 3 Data integration 4 Responsible AI 5 Product engineering

RECOGNIZED BY

Key concepts covered in this podcast

1

Agentic AI

How AI agents can act across workflows when systems, data, and permissions are connected.

2

Workflow automation

Where rule-based automation remains the better fit for predictable business processes.

3

GTM operations

How AI can reduce repetitive sales and revenue team admin work.

4

Integration strategy

Why connected systems are the foundation for scalable AI workflows.

5

Governance controls

How logging, access, observability, and entitlements reduce AI deployment risk.

6

Model flexibility

Why teams should avoid locking their architecture into one AI model or vendor.

7

ROI measurement

How leaders can prove value before scaling AI across teams.

Frequently Asked Questions (FAQs)

Is this episode only for technical leaders? Expand FAQ Collapse FAQ
No. It is also relevant for CEOs, revenue leaders, operations leaders, and transformation teams evaluating where AI can create measurable value.
What is the core focus of the episode? Expand FAQ Collapse FAQ
The episode focuses on Agentic AI, automation, integration, GTM workflows, governance, and practical AI adoption.
Can this help teams planning AI initiatives right now? Expand FAQ Collapse FAQ
Yes. It is useful for teams deciding where to use automation, where to use AI, and how to scale adoption without creating unnecessary risk.
Why is this podcast gated? Expand FAQ Collapse FAQ
It is offered as an on-demand resource for leaders researching AI agents, automation, workflow transformation, and business impact.

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