With Elena Alikhachkina — 4x Chief AI & Data Officer and Board Advisor

What does it really take to move from data projects to data products?

In this episode, Ben Parker speaks with Elena Alikhachkina about one of the biggest shifts happening across Data and AI and why technical expertise alone is no longer enough.

Drawing on more than 25 years in the industry, Elena explores how organisations can build more customer-focused, commercially relevant Data and AI products through stronger product thinking, business understanding and collaboration.

You’ll hear practical insights on:

• Why Data and AI teams need to think in products, not projects
• How to connect technical work to business outcomes
• Why product skills are becoming essential in AI
• Bridging the gap between business and technology
• The growing importance of communication and commercial awareness
• The skills future Data and AI leaders need to develop

Chapters

00:00 Introduction
01:33 Elena’s career and leadership journey
09:17 From data projects to data products
15:06 Building a product mindset in Data & AI
22:34 The skills Data & AI professionals need next
29:50 Bridging business and technology
34:00 Turning product thinking into business value

Thank you for listening!

With Phoenix Pei — SVP, Analytics Manager at Truist

What will the Data Scientist and Data Engineer of the future look like?

In this episode, Ben Parker speaks with Phoenix Pei about how AI and automation are changing data roles — and why technical expertise alone may no longer be enough.

Phoenix explores the growing importance of business understanding, trust and leadership alignment, why many data initiatives still struggle to create meaningful impact, and how organisations may need to rethink the structure of their data teams.

You’ll hear practical insights on:

• How AI and automation are changing Data Science and Data Engineering
• Whether the future belongs to specialists or full-stack data professionals
• The technical, business and leadership skills that will matter most
• Why so many data initiatives struggle to deliver business value
• What prevents Data Science projects reaching production
• How Data Scientists and Data Engineers will work together in the future

Chapters

00:00 Introduction
02:18 Phoenix’s career and leadership journey
09:34 How AI is changing Data Science & Engineering
11:08 Why business understanding matters more than ever
24:54 Why Data Science initiatives struggle to deliver
25:07 The importance of leadership alignment
33:53 Preparing Data teams for the future

Thank you for listening!

With Durai Rajamanickam — Senior AI Leader

How do leaders make better decisions about AI when the technology, risks and expectations are changing so quickly?

In this episode, Ben Parker speaks with Durai Rajamanickam about what it takes to turn AI ambition into something organisations can trust, scale and create value from.

They explore why AI initiatives can go wrong before technology is even the problem, the danger of hype-driven decisions, and why clear business objectives and leadership alignment matter.

The conversation also examines build vs buy, balancing speed with governance, when leaders should trust AI outputs, and the decisions organisations can't afford to delay.

You’ll hear practical insights on:

• Why organisations misdiagnose the problems they want AI to solve
• How to make better build-vs-buy decisions
• Why promising AI initiatives fail
• Balancing speed, innovation, governance and trust
• When leaders should trust or challenge AI outputs
• The AI decisions organisations need to make now

Chapters

00:00 Why AI strategies go wrong
01:09 Meet Durai Rajamanickam
03:46 Build vs buy in AI
05:36 Avoiding hype-driven AI decisions
07:41 Aligning AI with the business
09:11 Building trust and governance
12:22 Balancing speed with control
15:22 Making better decisions with AI
21:03 Advice for AI leaders

Thank you for listening!