In this episode of Data Analytics Chat, we welcome Elena Alikhachkina, a four-time Chief AI and Data Officer with Fortune 500 companies, and a board advisor. Elena shares her journey in data analytics and AI spanning over 25 years, covering key transitions in her career and the importance of blending business acumen with technical expertise. 

The discussion focuses on the critical shift from data projects to data products, highlighting the need for product skills in the age of AI. Elena emphasises the importance of understanding the business, building customer-centric solutions, and investing in both technical and soft skills for AI leaders. Her insights provide a roadmap for anyone looking to excel in data and AI roles in today's dynamic business environment.

00:00 Introduction to the Factory Process and Data Science Challenges
01:00 Welcome to Data Analytics Chat with Elena Alikhachkina
01:33 Ena's Career Journey and Insights
04:14 The Importance of Understanding Business Processes
09:17 Shifting from Data Projects to Data Products
11:08 The Need for a Product Mindset in AI
15:06 Challenges in Adopting a Product Mindset
16:39 Encouraging Proactivity and Collaboration
18:08 The Role of Education in Driving Change
22:34 The Need for Reeducation in Technology and Data
22:50 Embedding Data and AI in Business Curriculum
23:14 The Changing Role of Data in Leadership
24:01 The Importance of Soft Skills in Tech
25:31 Trust in Data and Technology
26:30 Essential Skills for the Future
28:20 The Shift to Product-Centric Roles
29:50 Bridging the Gap Between Business and Tech
30:16 Investing in Personal Development
31:19 Understanding the Customer's Needs
34:00 The Value of Product Thinking in AI
35:47 Career Growth Through Business Understanding
41:03 Final Thoughts and Call to Action

Thank you for listening!

In this episode of Data Analytics Chat, we’re joined by Phoenix Pei, SVP, Analytics Manager at Truist, to explore how the roles of Data Scientists and Data Engineers are changing in the age of AI and automation.

Phoenix explains why trust, leadership alignment, and business understanding are becoming more critical than technical skills alone, and how generative AI is reshaping how data teams work. We discuss which skills will matter most in the future, why so many data initiatives struggle to deliver impact, and how organisations should rethink team structure and collaboration to stay relevant.

A practical conversation for leaders and practitioners who want to build data teams that actually deliver value in an AI-driven world.

00:00 Introduction to Scaling Analytics and AI
00:50 The Role of Leadership in Data Science
01:24 Exploring the Future of Data Roles
01:46 Guest Introduction: Phoenix Pei
02:18 Phoenix's Career Journey and Insights
09:34 The Evolution of Data Roles with AI
11:08 The Importance of Business Understanding in Data Science
24:54 Challenges in Data Science Implementation
25:07 Leadership Alignment and Data-Driven Decisions
33:53 Preparing Data Teams for the Future
37:17 Conclusion and Final Thoughts

Thank you for listening!

In this episode of Data Analytics Chat, Ben speaks with Durai Rajamanickam, a senior AI leader, about what it really takes to turn AI ambition into something organisations can trust and scale.

They discuss why many AI initiatives fail long before the technology becomes the issue, the risks of hype-driven decision-making, and the importance of clear goals, strong business ownership, and measurable outcomes.

The conversation explores the tension between speed and governance, when to build vs buy, and why trust and governance are not obstacles to progress, but foundations for sustainable AI adoption.

This is a practical, experience-led discussion for leaders who want to build AI capabilities that last.

00:00 Introduction: The AI Hype and Strategy Revisions
01:09 Guest Introduction: Meet Durai Rajamanickam
02:09 AI Initiatives: Technical Capabilities and Investments
03:46 Build vs Buy: Evaluating AI Tools
05:36 Common AI Missteps: Hype and Misdiagnosis
07:41 Successful AI Implementation: Business and Technical Alignment
09:11 Governance and Trust: The Key to Sustainable AI
09:47 Real-World Examples: When AI Falls Short
12:22 Balancing Speed and Governance in AI
15:22 Decision-Making in AI: Trust and Autonomy
21:03 Final Thoughts: Advice for AI Leadership
23:04 Conclusion: Wrapping Up the Discussion

Thank you for listening!

Most organisations are experimenting with generative AI. Very few are turning it into a real business impact.

In this episode of Data Analytics Chat, we speak with Nayan Paul, Managing Director and Chief Architect for Generative AI at Accenture, about what it really takes to move from pilots to production.

They explore why GenAI adoption is fundamentally a leadership and operating-model challenge, not just a technology challenge, covering business ownership, data readiness, governance, and the balance between speed and responsibility.

This is a practical, honest conversation for leaders who want GenAI to become a real capability inside their organisation, not just another experiment.

00:00 Introduction to Generative AI Challenges
01:08 Guest Introduction: Nayan Paul from Accenture
01:46 Nayan Paul's Role and Responsibilities
05:08 Early Experiments and Lessons Learned
07:02 From Experimentation to Value Creation
10:14 Business Adoption and Technology Enablement
16:15 Framework for Successful AI Implementation
29:24 Balancing Speed with Responsibility
34:09 Advice for Moving from Curiosity to Impact
38:43 Conclusion and Final Thoughts

Thank you for listening!

In this episode of Data Analytics Chat, we welcome Sujit Narapareddy, Head of Data and Analytics at AWS Sales. Sujit shares his insights on AI transformation in large enterprises, likening it to the shift from paper maps to GPS. 

We discuss the critical role of human judgment in the age of AI, how organisations can effectively integrate AI into their workflows, and the importance of building a strong data foundation. Sujit shares his personal journey from a technical role to a leadership position, highlighting the importance of business intuition and continuous learning. 

The conversation covers how AI will change organisations by embedding insights into workflows and reducing the friction between knowing and acting. 

00:00 Introduction to AI Transformation
01:42 Guest Introduction: Sujit Narapareddy
02:08 Exploring AI's Impact on Organisations
02:32 Sujit's Career Journey and Leadership Insights
09:21 The Role of AI in Enhancing Human Roles
16:17 Challenges and Strategies for AI Integration
28:28 Preparing for the Future of AI
30:02 Conclusion and Final Thoughts

Thank you for listening!

In this episode of Data Analytics Chat, we welcome Carlos Pineda, the Head of Data Analytics and Insight at Diageo North America. Carlos shares his extensive experience in data analytics across Latin America, Asia-Pacific, Eastern Europe, and North America. 

They discuss the growing role of AI in both personal and corporate life, the importance of a strong data foundation, and the critical need to understand business processes and foster strong relationships. Carlos emphasises the importance of targeted AI use cases, end-to-end transformation, and continuous delivery in AI implementation. 

The conversation explores effective leadership strategies, experimentation, and the value of consistent stakeholder engagement to successfully integrate AI into business operations. Key topics include data readiness, the role of generative AI, and the overall impact of AI-driven business transformations.

00:00 Introduction to AI in Daily Life
01:15 Welcome to Data Analytics Chat
01:53 Meet Carlos Pineda
02:51 Career Decisions and Growth
05:30 Leadership Challenges and Lessons
08:02 The Reality of AI in Business
09:58 The Importance of Business Acumen
13:13 Challenges in AI Implementation
30:38 The Cost and Value of AI
33:39 Final Thoughts and Farewell

Thank you for listening!

In this episode of Data Analytics Chat, we welcome Misha Trubskyy, head of Claims Data Science at Mercury Insurance. Misha shares his journey from academia to corporate life, highlighting his transition from econometrics to leading data science initiatives in insurance. He discusses the significance of continuous learning, the challenges of implementing AI and data, and the importance of hiring and retaining top talent. Misha also delves into his leadership principles, the value of technical proficiency, and the importance of empathy in managing teams. Key issues such as the evolving hiring landscape, market conditions, and strategies for organisational growth are explored in-depth.

00:00 Introduction and Personal Philosophy
00:14 The Importance of Continuous Learning
00:44 Challenges in the AI and Data Science Field
01:20 Guest Introduction: Misha Ky
02:24 Misha's Career Journey
03:43 Current Excitements in AI and Data Science
06:09 Navigating Human Elements in Claims
07:37 Leadership Challenges and Lessons
11:28 The Value of Individuality in Leadership
19:31 Advice for Aspiring Data Leaders
29:52 Hiring Challenges in AI and Data Science
37:02 Finding the Right People for the Job
37:23 The Importance of Critical Thinking
37:41 Authenticity in Interviews
38:26 The Role of Technology in Interviews
38:51 Evaluating Candidates Beyond Technical Skills
41:36 The Misconception About Technical Skills
42:25 Personality and Attitude in Hiring
44:21 Challenges in the Job Market
48:55 Investing in Junior Staff
01:04:33 Retention Strategies for Top Performers
01:10:03 Future of the Hiring Landscape
01:13:42 Conclusion and Final Thoughts

Thank you for listening!

In this episode of Data Analytics Chat, we welcome Carol Kim, Executive Director at IBM, who shares her intriguing journey from a finance background to leading technology, data, and AI at IBM's Global Real Estate organisation. 

Carol discusses her career transformation, the importance of curiosity and authentic leadership, and the role of storytelling in decision-making. The episode also examines the significance of data governance and quality for data-driven decision-making, and how to build effective data governance frameworks. Carol further discusses adapting to different cultures, continuous reinvention, and the hidden costs of poor data quality. 

00:00 Introduction: The Power of Willingness to Learn
01:12 Welcome to Data Analytics Chat
02:01 Carol Kim's Career Journey
02:57 The Role of Data in Real Estate
03:38 Adapting to Different Cultures
07:54 The Importance of Storytelling in Data
09:59 Challenges in Leadership and Career Transitions
15:13 The Significance of Data Governance and Quality
24:06 Conclusion and Final Thoughts

Thank you for listening!

In this episode of Data Analytics Chat, host Ben welcomes Ilya Meyzin, SVP Head of AI Solutions at Dun & Bradstreet. Ilya shares his career journey from management consulting to leading AI solutions, highlighting the importance of implementation, continuous learning, and cross-domain expertise. He discusses the evolution of AI agents, their capabilities, and the shift from linear models to stateful, autonomous agents. The conversation delves into the complexities of scaling AI, embedding agents in enterprise architecture, and balancing technical innovation with business value. Ilya also emphasises the necessity of high-quality data and the importance of cross-departmental collaboration for successful AI deployment.

00:00 Introduction and Initial Insights
01:14 Guest Introduction and Career Overview
02:45 Transition from Strategy to Implementation
04:15 Learning and Adapting in Consulting
05:35 Defining Career Moments
10:35 Handling Challenges and Stress
13:03 Leadership and Team Dynamics
14:45 Balancing Technical and Business Skills
20:01 Focus and Credibility in Leadership
23:18 Introduction to AI Agents
23:39 Capabilities of AI Agents
24:22 Technical Aspects of AI Agents
25:39 Complex Problem Solving with AI Agents
28:40 High-Value Use Cases for AI Agents
32:14 Team Collaboration in AI Deployment
33:19 Challenges in Scaling AI Agents
37:21 Data Quality and AI Agents
45:12 Future of AI Agents in Enterprises
48:17 Conclusion and Final Thoughts

Thank you for listening!

In this episode of Data Analytics Chat, we sit down with Allison Olson, Senior Vice President of Analytics Solutions at Merkle. Allison shares her inspiring career journey, filled with proud moments, challenges, and valuable leadership insights. She talks about the importance of following your gut, taking risks, and how COVID-19 reshaped leadership attitudes.

We then discuss how AI is transforming personalisation and, ultimately, buying behaviour. Allison breaks down the shift from static to dynamic personalisation, exploring how adaptive experiences powered by real-time data guide customer decisions. She also covers the ethical use of AI, strong data foundations, and the transformative role of generative AI in creating truly tailored customer experiences that influence what we buy and why.

00:00 Introduction to Leadership and Personal Growth
00:21 The Role of Gut Instinct in Decision Making
00:52 Challenges and Ethical Concerns in Data Analytics
01:34 Welcome to Data Analytics Chat
02:12 Alison Olson's Career Journey
04:46 The Evolution of Leadership
07:11 Impact of COVID on Leadership
08:37 Learning from Failures and Taking Risks
10:37 Balancing Management and Leadership
13:45 Skills and Mindsets for Leadership
16:32 Advice for Aspiring Leaders
21:01 Introduction to Dynamic Personalisation
21:59 The Concept of Dynamic Personalisation
23:23 Static vs. Dynamic Personalisation
25:34 Real-World Examples of Personalisation
27:22 Data Types for Adaptive Experiences
29:27 Predictive Signals for User Needs
30:42 Balancing Personalisation and Privacy
35:12 Challenges in Real-Time Personalisation
38:16 Generative AI and Future Possibilities
40:05 The Future of Jobs in Data and Analytics
43:57 Conclusion and Final Thoughts

Thank you for listening!