ON DEMAND • Podcast Episode

AI for Sales Teams That Want to Win: The Revenue Advantage

Abigail Merrill, Founder of Growth Up Partners, joins Better Tech to discuss how growing businesses can use AI to improve sales workflows, reduce admin work, and turn scattered experimentation into measurable revenue impact.

FEATURED GUEST

Abigail Merrill

Our featured guest

Abigail Merrill

Founder, Growth Up Partners

Abigail Merrill brings a revenue-focused perspective to AI adoption. In this episode, she explains why successful AI initiatives do not start with tools alone. They start with alignment, workflow clarity, responsible use, and measurable business goals.

She also covers:

  • Why AI adoption fails when teams skip alignment
  • How revenue teams can reduce repetitive admin work
  • Why existing tools may already hold the first AI use cases
  • Where governance risks appear in everyday AI use
  • How to move from pilot to process without losing human judgment

Why this conversation matters now

Growing businesses are under pressure to move fast on AI, but many teams are still stuck in disconnected pilots, unclear ownership, and low adoption.
This episode explores the questions leaders are asking now:

01.

Where should AI actually be used first?

02.

How do we know if leadership, managers, and users are aligned?

03.

Can AI improve revenue workflows without adding complexity?

04.

Are we getting enough value from tools we already own?

05.

What data and security risks are we missing?

06.

How do we scale AI without removing human judgment?

What you'll learn in this episode

01.

Why AI adoption should start with alignment before tool selection

02.

How SMART goals reveal whether teams are working toward the same outcome

03.

Why idle experimentation does not create scalable AI value

04.

How sales and marketing teams can use AI to reduce admin work

05.

Why companies should review existing tools before buying new platforms

06.

How everyday AI integrations can expose sensitive business content

07.

Why pilots need owners, baseline metrics, reports, and workflow boundaries

Who this episode is for

CEOs and business leaders CTOs and CIOs Revenue and sales leaders Operations leaders Digital transformation teams Growing businesses exploring AI adoption

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 key takeaways

01.

Alignment is the real starting point

AI adoption becomes easier when teams share a clear goal. Abigail explains why she starts by understanding motivation, readiness, friction, and workflow gaps before implementation begins.

02.

AI should support revenue workflows

For sales and marketing teams, the opportunity is not just automation. It is reducing admin work, improving follow-ups, finding the right content faster, and giving teams more time with customers.

03.

Existing tools may already hold the first use cases

Many companies already have AI features inside platforms like CRM, Copilot, Salesforce, and productivity tools. The gap is often training, enablement, and knowing which workflow to improve first.

04.

Governance risks can appear in small actions

A simple connection between a work tool and a personal AI account can expose contracts, quotes, internal slides, and proprietary business content.

05.

Scaling requires pilots, metrics, and SOPs

Abigail’s approach moves through alignment, integration, and scale. The goal is to test focused use cases, measure against baseline data, document what works, and build repeatable processes.

Why tkxel is hosting this conversation 

 tkxel helps growing businesses move AI from pilots into real workflows through strategy, data readiness, product engineering, and responsible implementation.

This episode reflects the same challenge many teams face today: AI tools are available, but adoption stalls when goals, workflows, governance, and change management are unclear. Abigail’s perspective adds practical context for leaders trying to reduce revenue team admin work, improve adoption, and turn AI experiments into measurable business impact without losing human judgment.

WHERE TKXEL BRINGS CONTEXT

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

RECOGNIZED BY

Key concepts covered in this podcast

1

AI adoption

How teams move from experimentation to measurable business use.

2

Revenue operations

Where AI can reduce admin work and improve sales productivity.

3

Workflow alignment

Why leadership, managers, and users need shared goals before implementation.

4

Governance risk

How everyday AI use can expose sensitive business data.

5

Pilot measurement

Why baseline metrics and ownership matter before scaling.

6

Human judgment

Where people still need to guide decisions, relationships, and customer conversations.

7

Change management

How teams build trust, adoption, and readiness before scaling AI across workflows.

Frequently Asked Questions (FAQs)

Is this episode only for technical leaders? Expand FAQ Collapse FAQ
No. It is highly relevant for CEOs, operations leaders, revenue leaders, and transformation teams evaluating how AI can improve business workflows.
What is the core focus of the episode? Expand FAQ Collapse FAQ
The episode focuses on practical AI adoption for growing businesses, including alignment, revenue workflows, governance, pilots, measurement, and scaling.
Can this help teams planning AI initiatives right now? Expand FAQ Collapse FAQ
Yes. It is useful for teams trying to move beyond experimentation and think clearly about goals, workflows, ownership, safety, and ROI.
Why is this podcast gated? Expand FAQ Collapse FAQ
It is offered as an on-demand resource for leaders researching AI adoption and measurable business impact.

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