What does the near term future of Enterprise AI look like? A scramble to get valuable, cost-effective, enterprise-grade AI solutions into production, with rigorous governance at scale. If that sounds like a tall order - that’s because it is! However, large advanced organizations (yes, even outside of the tech sector) are already seeing success deploying AI solutions and we can expect the pace to accelerate rapidly in the next 1-2 years.

To find out how enterprises are gearing up for this challenge we speak with Richard Swakla, AI and ML Specialist at NetApp and get the inside scoop on the trends that are underway and the strategies organizations are putting in place to operationalize meaningful AI outcomes.  
Join us as we discuss:

• The pressure to shift from experimentation to production
• Breaking down the data, infrastructure and organizational silos
• Best practices for tackling governance, security and cost challenges
• Examples of AI efficiency gains in healthcare, pharma, and beyond

AI is transforming financial services and insurance, but rarely in the headline-grabbing ways you might expect. From intelligent process automation to fraud detection and risk management, AI is being embedded across operations, but as AI adoption grows, so do the challenges—cybercrime, rapid technological changes, and ever-evolving regulatory frameworks.

In this episode we sit down with Adam Gale, Field CTO for AI & Cyber Security at NetApp, and Mike Upchurch, VP of Strategy for Financial Services and Insurance at Domino, to explore:

• The "silent revolution" of AI in finance
• Unlocking the potential of unstructured data
• AI governance for innovation and regulatory compliance
• Strategies for driving AI adoption
• Top predictions for AI in 2025 in FSI

AI is transforming drug discovery and clinical trials, making what was once cutting-edge the new standard. Pharma companies are evolving into tech companies, leveraging AI to revolutionize every phase of drug development.

In this episode, Chris McSpiritt, VP of Life Sciences Strategy at Domino, discusses how AI is no longer a niche capability for select firms but an essential capability for all biopharma organizations. We explore AI-based digital organisms, the increasing reliance on AI in clinical trials, and the shift toward personalized medicine.

Join us as we dive into:

• How AI will drive the majority of new drug discoveries
• The role of AI in clinical trials
• The growing need for pharma companies to adopt a tech company mindset
• The impact of AI-driven automation on regulatory compliance and reporting

What’s next for artificial intelligence in 2025? In this episode, Dr. Kjell Carlsson delivers his annual predictions about the immediate future of AI. From AI becoming the universal corporate scapegoat to the rebranding of generative AI as "agentic AI.” Discover why commercial AI solutions remain scarce, the pivotal role of workforce upskilling in achieving transformative AI outcomes, and how governance is shifting from regulation-focused to impact-driven.

Want to see how Kjell fared in his 2024 predictions? Look no further than Data Science Leaders podcast Episode 62: AI in 2024: Predictions on the Future of the AI Revolution.

Innovation and AI governance aren’t at odds. Done properly, governance practices can be the key to accelerating implementation of even the latest GenAI use cases. In this interview from RevX London with Raj Mukherjee, Head of Data Science and AI at Direct Line Group, we find out how they embraced the principles of a lean startup, adopted a product mindset and became the first major insurance company to implement a GenAI solution to accelerate customer service. Come find out how they were able to overcome the challenges of legacy infrastructure, build trust and do the seemingly impossible — make compliance fun.

How can organizations drive transformative AI innovation while effectively managing its inherent risks? Is governance a bottleneck or can it become a catalyst for AI success?
In this webinar, we explore the critical role of AI governance with Brandon Purcell, VP Principal Analyst at Forrester Research, and Theo Linnemann, Data Scientist at the Federal Reserve Bank of New York. Together, they share actionable insights into the principles, practices, and policies necessary for ensuring the safe use of AI that drives real-world impact.

Join us as we discuss:

• The evolution of AI governance and why it has become a top priority for AI teams
• Frameworks and practices for identifying and managing AI risk 
• The growing importance of automation for effective governance
• Fairness, business, and other metrics for AI governance
• How to govern an Agentic AI future 

This episode is a collaboration with the Ethical Machines podcast featuring Reid Blackman — CEO of the AI ethical risk consultancy Virtue — and Nick Elprin, cofounder and CEO of Domino Data Lab.

Join us as they discuss:

• The differences between AI ethics and AI governance
• How the AI governance challenges have changed (and where they haven’t)
• The people, process and technology solutions for genAI governance (and how they are all intertwined)
• Predictions about AI maturity, slip ups and regulation

Think you have a hard time driving AI adoption in your organization? Try driving AI transformation in the largest, most regulated organization on the planet – the Pentagon. 

In this episode, we sit down with Dr. Chris Kirchhoff – co-author of Unit X: How the Pentagon and Silicon Valley are Transforming the Future of War and former Director of Strategic Planning for the National Security Council – to uncover how the Department of Defense is accelerating the adoption of AI. Dr. Kirchhoff shares invaluable lessons on managing disruption and fostering innovation at scale.
Join us as we discuss:

• How leadership and experimentation drove the success of the Defense Innovation Unit
• The importance of developing new frameworks for procurement for AI adoption
• Insights from modern warfare: drone technology and the shift to consumer-driven innovation
• Best practices for scaling technological transformation across any large organization

The EU AI Act, is it the first step towards comprehensive AI regulation that will make us all safer, or is it the scariest thing in AI today, or both?

In this episode we speak with Adam Gale, Field CTO for AI and Regulatory Compliance at NetApp, to demystify the EU AI act and discuss future-proof strategies to ensure compliance.Join us as we discuss:

• The core requirements of the act and how they impact your use cases
• Gray areas to look out for in the act
• Compliance with existing regulations such as DORA and GDPR
• Core governance capabilities that enable compliance for the EU AI act and future regulation

AI governance is no longer a hypothetical consideration—it's critical not only to meet regulatory requirements but also to build trust, drive adoption, and deliver tangible impact with AI. In this episode, we bring together experts Jared Vaudrey and Dr. Dylan Bobby Storey, who have spent years developing AI solutions in heavily regulated industries. They share their hard-won insights on the realities of implementing AI governance across a wide range of organizations and use cases.

Join us as we discuss:

• The value of AI governance for driving adoption and innovation
• How governance principles apply to traditional ML and genAI
• The common challenges of governance 
• Real-world examples and best practices from advanced teams integrating AI governance
• How automation helps scale governance and provide the flexibility to support future regulation

AI governance is more important than ever, but confusion reigns about basic questions such as: what it is, why it is important and what we should do about it. As an AI, data science, or business leader, you need to dispel these governance misconceptions in order to manage AI risk and ensure the safety and reliability necessary to drive adoption and impact. The ability of your organization to drive impact with AI, and potentially your career, depends on it.

Join us as host Kjell Carlsson, gives an opinionated take on the basic questions of AI governance:

• Why you should care about AI governance (and why it goes beyond ethics and regulation)
• What AI governance is (and how it differs from ethical AI, responsible AI, and trustworthy AI)
• Why AI governance is difficult (and the gap between frameworks and practices)
• What AI governance looks like in practice (across the AI/ML lifecycle)
• What we need for AI governance (and the capabilities to do it at scale) 

  

Data privacy - why is it so important in the age of AI, why is it so difficult, and what should we be doing to improve it in our organizations?

In this episode we speak with Dr. Rebecca Balebako, privacy engineer and Chief Privacy Officer at Lotic.ai, about why AI makes privacy more important than ever, the common misconceptions around data protection, who should own privacy, and the benefits and limitations of privacy enhancing technologies (PETs).

Join us as we discuss:

• The value of privacy (~5% of annual profit)
• The many definitions of privacy.
• The top 3 misconceptions: no one cares, it can be fixed with a privacy policy, and privacy is a blocker.
• Who should own privacy in your organization.
• PETs vs. data hygiene

For more on Rebecca’s consulting on privacy strategy, coaching and how to build a privacy advocate team see https://www.privacyengineer.ch/ and for more on privacy methods check out the book “Practical Data Privacy” by Katharine Jarmul.

What capabilities do you need to take advantage of AI and what changes will you need to make to your IT architecture? Well, let’s look at the data.

In this episode, Shawn Rogers, CEO and Fellow at BARC US, shares the results of their survey on how enterprises are optimizing their architecture for AI innovation. Shawn unpacks data on everything from the biggest obstacles to delivering AI impact to how companies are sourcing their AI capabilities. 

Join us as we discuss:

• The AI talent gap and the strategies that firms are using to close it
• The myriad AI capabilities that high-readiness firms are implementing
• The need to manage AI costs upfront to ensure deployment
• The perpetual question of build vs. buy (or both!)
• The crucial need for AI governance to ensure approval and adoption

Download the full report here.

How do you drive digital strategy and transformation with AI? Do you need an AI strategy or a business strategy that intelligently leverages AI?

In this episode, we delve into the challenge of driving transformation with AI in insurance with Fu'ad Butt, VP Head of Digital Strategy and Automation at OneAmerica. Fu’ad shares his best practices for identifying and executing AI projects. These range from how to identify the most promising use cases (hint: focus on augmented intelligence, but tie it to business value) to executing them successfully (build a test and learn process, and use multifunctional pods).  

Join us as we discuss:

• The role of AI in digital strategy today.
• Overcoming the challenge of aligning AI to business value.
• Experimenting efficiently with digital twins and a contrarian in the loop.
• Breaking hierarchies with multifunctional pods for faster impact.

AI is disrupting marketing, but the biggest threat isn’t AI systems misbehaving, it is the unintended consequences of AI systems performing exactly what they were intended to do.

In this interview with Dr. Daniel Hulme, Chief AI Officer at WPP and CEO of Satalia, we discuss the ways that AI is transforming marketing – from accelerating content creation and maximizing activation to exploring the creative landscape and creating “brains” that ensure it is responsible and legal. Also, tune in for fascinating discussions of AI consciousness and what it means to be a Chief AI Officer.    

Join us as we discuss:

• The greatest GenAI opportunities in marketing and beyond
• How to maximize AI impact with decision optimization
• Responsible AI and the challenges of AI systems going very right
• The emerging field of AI consciousness
• The Chief AI Officer: why you need one and the prerequisites for success  

For more information about the new research organization focused on AI consciousness co-founded by Daniel Hulme see conscium.com and his interview on the London Futurists Podcast.

How do you deliver impact with AI and ML and cut development time by weeks and even months? By understanding your customer, building trust, and managing risk. 

Done well, effective and responsible AI practices can be the secret to faster implementation, adoption, and performance at lower cost and risk.

In this episode with Dr. Alex Manasson, Data Science Leader for the Americas at International Flavors and Fragrances (IFF), we uncover their best practices for managing risk and driving rapid AI development and adoption in the safety-focused world of manufacturing.. Dr. Manassof shares insights on balancing statistical process control with predictive modeling, the importance of adapting your data collection processes, and the pros and cons of digital twins. Discover practical tips and strategies for implementing AI and ML tools to boost efficiency and foster trust in high-stakes environments.