ON DEMAND • Podcast Episode

Unlock the Power of Your Data: Private AI Without Losing Control

A candid conversation with Oliver King-Smith, Founder of Smarter AI, on private AI, small language models, assistive intelligence, AI pilots, workforce impact, and why successful AI adoption starts with focused business problems.

FEATURED GUEST

Oliver King-Smith

Our featured guest

Oliver King-Smith

Founder, Smarter AI

In this episode, Oliver King-Smith shares a practical view on building AI systems that support employees, solve focused data problems, and operate inside private environments.

Drawing from his background in mathematics, technology consulting, startups, and AI application development, Oliver explains why Smarter AI focuses on assistive intelligence and private AI solutions for industries where data control, security, and specialized workflows matter.

He also covers:

  • Why AI should be treated as assistive intelligence
  • How private AI helps organizations keep sensitive data in their own environments
  • Why small language models can be more practical than large models for specific use cases
  • How companies can move AI pilots into production
  • Where AI may create new demand for data and business analysts

Why this conversation matters now

Many organizations want to adopt AI, but the harder question is where AI actually belongs and how to use it without losing control of sensitive data.

01.

Should AI replace work, or assist the people doing it?

02.

When does a small language model make more sense than a large model?

03.

How can sensitive industries use AI without sending data to public platforms?

04.

Why do so many AI pilots fail before production?

05.

Where should companies start if they want measurable ROI?

06.

How will AI reshape jobs, skills, and future workforce needs?

What you'll learn in this episode

After unlocking the full podcast, you’ll get expert insights on private AI, small language models, secure deployment, and practical AI adoption.
01.

Why Smarter AI frames AI as assistive intelligence, not artificial replacement

02.

How private AI keeps data within an organization’s own environment

03.

Why smaller, specialized models can reduce cost, power usage, and complexity

04.

How AI modules can work alongside traditional software code

05.

Why sensitive industries need stronger data privacy and control

06.

How focused use cases improve the odds of AI reaching production

07.

How AI may create new demand for data analysts and business analysts

Who this episode is for

CEOs and business leaders CTOs and CIOs Aerospace and defense leaders Healthcare and medical technology leaders Data and analytics leaders Teams planning private AI initiatives Growing businesses moving AI pilots into production

Our host

Haseeb Khan 1

Haseeb Khan

VP, Technology

Haseeb Khan is a founding member and Vice President of Technology at tkxel with over 23 years of experience in software engineering and technology leadership. He has played a key role in shaping tkxel’s engineering foundations, delivery standards, and technical culture. His expertise covers enterprise platforms, distributed systems, mobile solutions, legacy modernization, and AI/ML.

A preview of the key takeaways

01.

AI works best when it assists people

Oliver argues that AI becomes more powerful when it helps people achieve better results, instead of being treated only as a way to remove headcount.

02.

Private AI matters for sensitive environments

For aerospace, defense, medical, and education use cases, organizations often need AI systems that run inside their own infrastructure or private cloud tenancy.

03.

Small models can be the right models

Smaller, specialized models can be more cost-effective and easier to deploy for focused workflows, especially when the model does not need to solve every possible problem.

04.

AI should be combined with traditional software

Smarter AI approaches AI as part of a broader software stack. Traditional code handles what it does best, while AI components add new capabilities.

05.

Production AI starts with the right workflow

AI projects are more likely to succeed when teams start with a focused workflow, reduce risk, prove value, and build on early success.

Why tkxel is hosting this conversation 

 At tkxel, we work with growing businesses navigating AI adoption, data security, software engineering, cloud modernization, and workflow transformation.

This episode is especially relevant for leaders trying to move beyond AI experimentation and build secure, practical AI systems. It is not just a conversation about language models. It is a business conversation about data control, focused implementation, workforce readiness, and using AI to help people perform better.

WHERE TKXEL BRINGS CONTEXT

1 Private AI strategy and implementation 2 Secure software and cloud architecture 3 Data readiness and workflow transformation 4 AI pilot planning and production delivery

RECOGNIZED BY

Key concepts covered in this podcast

1

Private AI

Explains how AI systems can operate inside controlled environments without exposing sensitive data to public platforms.

2

Small language models

Covers why focused, smaller models can be more practical for specific business workflows.

3

Assistive intelligence

Shows why AI should support employees and improve decision-making instead of being framed only as replacement.

4

Secure AI deployment

Explores how sensitive industries can use AI while maintaining stronger control over data, infrastructure, and access.

5

AI pilots

Looks at why many AI pilots stall and how focused workflows can improve the path to production.

6

Human and workforce impact

Covers how AI may change roles, increase demand for analysts, and reshape how teams work with data.

7

Business-led AI adoption

Explains why AI initiatives should start with a clear problem, measurable value, and the right deployment model.

Frequently Asked Questions (FAQs)

Is this episode only for technical leaders? Expand FAQ Collapse FAQ
No. While the conversation covers private AI, small language models, and secure deployment, it is also relevant for CEOs, operations leaders, data teams, healthcare leaders, aerospace and defense teams, and business leaders evaluating AI adoption.
What do I get after accessing the podcast? Expand FAQ Collapse FAQ
You get access to the full podcast episode and transcript.
What is the core focus of the episode? Expand FAQ Collapse FAQ
The core focus is private AI, small language models, assistive intelligence, AI pilots, secure deployment, and workforce impact.
Why is the podcast gated? Expand FAQ Collapse FAQ
It is positioned as a premium resource for leaders actively researching private AI, secure AI adoption, and practical AI implementation.
Can this help teams planning AI pilots? Expand FAQ Collapse FAQ
Yes. The episode is useful for teams thinking about use case selection, data privacy, model choice, deployment environment, ROI, and how to move pilots into production.

Access the full podcast

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