AI adoption is moving so quickly that, for many organisations, governance is struggling to keep pace. So how can leaders begin thinking more strategically about how, when, and even if they use AI?

In this episode of Tech Tomorrow, David Elliman speaks with responsible AI expert Zahra Shah about what it takes to adopt AI safely and responsibly, and to deliver real business value.

Zahra explains that rapid AI development is making it harder for businesses to keep up with evolving risks, regulations, and operational demands. At the same time, ‘shadow AI’ is on the rise, as employees use generative AI tools without oversight, increasing the risk of exposing sensitive company or customer data.

Zahra stresses that successful AI adoption starts with the basics: clear use cases, proper due diligence, and strong governance from the outset. She also recommends starting with a requirements analysis, establishing responsible AI principles such as transparency and explainability, and implementing safeguards against bias, hallucinations, and compliance risks before scaling.

Rather than launching sweeping transformation programmes, she encourages businesses to begin with smaller, lower-risk pilots that deliver measurable outcomes. Internal HR policy assistants, for example, can help teams test workflows in a safe environment while also teaching employees not to treat AI like ‘Google 2.0.’

Another major theme in this episode, and throughout Season 3, is avoiding vendor lock-in. Zahra recommends using abstraction layers so organisations can switch providers as the market evolves while retaining control over prompts, evaluations, and proprietary data. She argues that accountability should remain with business owners, supported by cross-functional governance groups spanning technical, legal, compliance, and operational teams.

Finally, the conversation explores the UK context and how it could build confidence in AI through trust marks, certification, and regional workforce development. Zahra points to Singapore as a strong example of practical, agile AI governance in action.

Episode Highlights

01:18 – The staggering speed of AI deployment.

04:07 – Small pilots are a good policy.

06:40  – Data hygiene and AI governance.

08:39 – David’s Thoughts: The problem of vendor lock-in.

10:03  – Not every company needs a large language model.

11:27 – AI ethics and the fear of accountability.

14:27 – The global picture of AI regulation.

18:07 – David’s Thoughts: Regional employment inequality in the UK.

19:02 – The global erosion of trust in AI.

20:31 – Are leaders deploying AI faster than they can effectively govern it?

About Zühlke:
Zühlke is a global transformation partner, with engineering and innovation at its core. We help clients envision and build their businesses for the future – running smarter today while adapting for tomorrow’s markets, customers, and communities.

Our multidisciplinary teams specialise in technology strategy and business innovation, digital solutions and applications, and device and systems engineering. We thrive in complex, regulated sectors such as healthcare and finance, connecting strategy, implementation, and operations to help clients build more effective and resilient businesses.

Links:

• Zühlke Website
• Zühlke on LinkedIn
• David Elliman on LinkedIn
• Zahra Shah on LinkedIn

In a tech industry driven by profit, can companies really prioritise social impact over shareholder value?

In this episode of Tech Tomorrow, David Elliman sits down with serial social entrepreneur and author Jim Fruchterman to explore what ‘tech for good’ really means, and whether it can truly exist within traditional, venture-backed business models.

Drawing on his experience building an OCR (Optical Character Recognition) startup, Jim explains how a venture capital board shut down a reading machine for blind users after deciding the market was too small. That experience eventually led him to launch a nonprofit focused on accessible technology, demonstrating that mission-driven organisations can still operate within Silicon Valley systems while benefiting underserved communities.

The conversation also examines how investor incentives can unintentionally steer companies towards harmful outcomes, even when the people inside them have good intentions. Jim highlights alternative models, including B Corps, Pledge 1%, and treating social impact as a core business metric rather than a marketing add-on, as ways to help counteract this.

Jim also shares examples of tech partnerships in which engineers and product teams offered steep discounts or free licenses to nonprofits because they believed in the mission and took pride in building useful tools. At the same time, he notes that large companies have sometimes scaled back or removed nonprofit-friendly pricing entirely once those markets became more commercially attractive.
The conversation also explores which problems are best addressed through for-profit innovation, such as clean energy, and which may always rely on charities and nonprofits, including human rights advocacy. 

Overall, Jim emphasises that the wider tech ecosystem, from smartphones and app stores to open-source software, plays a vital role in making meaningful social impact possible.

Episode Highlights

01:18 – What is ‘tech for good’?

01:45 – Jim’s social entrepreneur origin story.

05:46 –  Jim’s mantra: ‘Try to do good on purpose rather than evil by accident’.

07:59 – David’s Thoughts:  Switching focus from profit to other measures of value.

09:29 – Can every part of the tech industry do societal good?

10:53 – The power of reducing software costs for nonprofits.

15:15 – David’s Thoughts:  Most of the engineers don't get out of bed for the share price.

16:13 – What else could be done to help regulate big tech?

20:13 – Is it possible for tech for good to exist within a for-profit model?

About Zühlke:
Zühlke is a global transformation partner, with engineering and innovation at its core. We help clients envision and build their businesses for the future – running smarter today while adapting for tomorrow’s markets, customers, and communities.

Our multidisciplinary teams specialise in technology strategy and business innovation, digital solutions and applications, and device and systems engineering. We thrive in complex, regulated sectors such as healthcare and finance, connecting strategy, implementation, and operations to help clients build more effective and resilient businesses.

Links:

• Zühlke Website
• Zühlke on LinkedIn
• David Elliman on LinkedIn
• Jim Fruchterman Website
• Jim Fruchterman LinkedIn
• The Tech Matters Podcast
• Technology for Good: How Nonprofit Leaders Are Using Software and Data to Solve Our Most Pressing Social Problems Book

Many people see artificial intelligence as a tool for making decisions faster and more logically. But what if we’ve misunderstood what AI really is and how to use it well?

In this episode of Tech Tomorrow, David Elliman talks with Stephanie Antonian, Founder and CEO of Aestora, about whether AI really improves how we think. Focus on the arguments made in Stephanie’s essay, AI is Irrational, which questions the idea that AI always follows traditional logic. Instead, she explains that most modern AI, especially machine learning, finds patterns and makes predictions based on past data rather than relying on strict logical reasoning.

They discuss how this change has confused many business leaders, who expect certainty from AI systems that operate on probabilities and don’t provide fixed answers. This misunderstanding has led to overinvestment, failed AI projects, and frustration with unclear or inconsistent results.

David and Stephanie also look at what this means for accountability and governance. Stephanie stresses the need for real human oversight, transparency, and the ability to audit AI systems. Instead of only engaging in abstract ethical debates, Dave suggests a practical approach grounded in safety engineering, such as traceability and thorough testing.

The episode features practical advice for leaders who want to use AI responsibly. Stephanie suggests that organisations should compare costs and capabilities, run controlled tests, and focus on current performance factors like accuracy and integration before expanding. She also warns that without careful management, AI can make organisations more complex and lead to analysis paralysis rather than better decisions.

Episode Highlights

01:28 – The core arguments of AI is Irrational.

03:30 – Is it the tools we use, or the human interaction with them, that causes issues?

05:06 – What are some use-cases for machine learning tools?

07:09 – David’s Thoughts: The current state of play in AI.

08:29 – We need outliers, not probabilities, to make the world better.

10:45 – There always needs to be a human in the loop.

14:57 – David’s Thoughts: The AI ethics debate.

16:05 – What can business leaders actually do about all of this?

18:21  – Is irrational AI making our decision-making worse?

About Zühlke:

Zühlke is a global transformation partner, with engineering and innovation at its core. We help clients envision and build their businesses for the future – running smarter today while adapting for tomorrow’s markets, customers, and communities.

Our multidisciplinary teams specialise in technology strategy and business innovation, digital solutions and applications, and device and systems engineering. We thrive in complex, regulated sectors such as healthcare and finance, connecting strategy, implementation, and operations to help clients build more effective and resilient businesses.

Links:

• Zühlke Website
• Zühlke on LinkedIn
• David Elliman on LinkedIn
• Stephanie Antonian on LinkedIn
• Aestora Website
• AI is Irrational Essay
• MIT report: 95% of generative AI pilots at companies are failing Article 

As agentic AI gets more advanced, how do we decide where its independence should start and stop?

In this episode of Tech Tomorrow, David Elliman speaks with consultant and author Sam Newman about setting boundaries for agentic AI in large-scale systems. They also discuss why planning for uncertainty is now a key issue for many business leaders, and how doing small experiments with AI is ultimately the best approach.

Sam points out that non-determinism in agentic AI is a major challenge because its results are not always predictable. When these AI workflows are connected, small mistakes early on can spread and impact later parts of the system. To handle this, Sam suggests breaking systems into smaller, manageable parts and adding checks between steps to catch problems early. He also highlights the importance of being able to trace issues and roll back changes, so teams can fix problems and recover from failures. These steps are only possible if boundaries are set early and humans stay in the loop throughout.

They also talk about designing systems, so AI does not become a complicated dependency. One way is to keep AI tasks separate, using clear boundaries and security measures, often treating them as their own services within specific business areas. This makes it easier to manage data securely and to swap out models or vendors as technology changes and providers rise and fall.

Of course, costs make things even more complicated. Token-based pricing models can lead to unpredictable expenses, much like the early days of cloud computing, where many businesses were shocked that the promise of cost-cutting wasn’t delivered on. Subscription models for AI software can also hide high computing costs, making it hard for decision-makers to know how much they are really spending on agentic AI.

Overall, Sam’s main point is clear: try small, controlled experiments with agentic AI, but do not let them manage your large-scale systems without oversight, clear boundaries, and a way to undo changes if something goes wrong.

Episode Highlights

01:17 – How are agentic AI agents defined, and what is determinism in this context?

03:56  – What kind of issues are Sam’s clients having?

07:13  – The shift to breaking down problems into lots of modular steps.

08:48  – David’s Thoughts: What happens when AI agents pass problems down the chain?

10:12 – How does Sam approach agentic agent deployment?

16:32  –  Sometimes it just makes sense to write the code yourself.

19:30  – David’s Thoughts: Lessons learned from the move to the Cloud.

21:06  – Where Sam thinks generative AI may be heading.

25:36 – Sam’s advice on agentic AI? Do lots of small experiments.

26:56 – Wrap up.

About Zühlke:
Zühlke is a global transformation partner, with engineering and innovation at its core. We help clients envision and build their businesses for the future – running smarter today while adapting for tomorrow’s markets, customers, and communities.
Our multidisciplinary teams specialise in technology strategy and business innovation, digital solutions and applications, and device and systems engineering. We thrive in complex, regulated sectors such as healthcare and finance, connecting strategy, implementation, and operations to help clients build more effective and resilient businesses.

Links:

• Zühlke Website
• Zühlke on LinkedIn
• David Elliman on LinkedIn
• Sam Newman Website

An estimated 55 million people worldwide are living with dementia, of which Alzheimer’s is the most common form. This number continues to rise as global populations age. Despite the scale of the problem and large amounts of funding, no one has been able to find a cure. Could it be that data science, rather than medicine, holds the answers to tackling this disease?

In this episode of Tech Tomorrow, David Elliman speaks with Alejo Nevado-Holgado, Associate Professor of Psychiatry at the University of Oxford and member of the Big Data Institute. He leads AI research within the Computational and Molecular Neuroscience Laboratory, an interdisciplinary team spanning AI, biochemistry, and bioinformatics.

The conversation explores how advanced computational methods are using vast biological and clinical datasets, including genomics, transcriptomics, proteomics, stem cell imaging, brain scans, and electronic health records. This integrated approach aims to uncover disease mechanisms, identify new drug targets, and advance more personalized treatments, all supported by high-performance computing.

A key challenge in Alzheimer’s research is the difficulty of accessing and studying the brain. The blood-brain barrier limits treatment delivery, while the disease develops over decades before symptoms appear. The discussion also highlights ongoing scientific uncertainty about whether hallmark features such as amyloid plaques and tau tangles are causes of the disease or downstream effects.

The episode examines how AI can support early detection through blood-based biomarkers and why it is particularly effective in analysing complex, high-dimensional data such as molecular structures and genomic information. The importance of combining diverse datasets, such as population-scale biobanks and drug discovery data, is emphasised as essential for progress.

However, challenges remain, including the need for explainable AI systems and more complete longitudinal health data. The conversation also touches on emerging techniques like AI-driven molecular simulations, which may help predict how drugs interact within the brain.

Episode Highlights

01:07 – The background of Alejo’s project.

02:25 – Why are Alzheimer's and dementia so hard to treat?

05:50 – How can neurodegenerative brain diseases be prevented?

07:05 – Drug discovery and machine learning.

09:43 – David’s Thoughts: Multi-modal data.

10:29 – Why high-quality data is so hard to access.

14:55 – Why AI explainability remains an issue.

17:06 – David’s Thoughts: A black box within a black box.

19:23 – The UK Biobank and rich medical data.

23:54 – Wrap up.

About Zühlke:

Zühlke is a global transformation partner, with engineering and innovation at its core. We help clients envision and build their businesses for the future – running smarter today while adapting for tomorrow’s markets, customers, and communities.

Our multidisciplinary teams specialise in technology strategy and business innovation, digital solutions and applications, and device and systems engineering. We thrive in complex, regulated sectors such as healthcare and finance, connecting strategy, implementation, and operations to help clients build more effective and resilient businesses.

Links:

• Zühlke Website
• Zühlke on LinkedIn
• David Elliman on LinkedIn
• Prof. Alejo Nevado-Holgado Bio
• Dementia Research Oxford Website
• UK Biobank Website

Join David Elliman as he continues exploring the fast-changing world of emerging tech.  With his five new guests, he’ll dive into topics like the role of agentic systems, how AI’s irrationality is making our decision-making worse, and whether tech for good is even possible in a for-profit business.

About Zühlke:

Zühlke is a global transformation partner, with engineering and innovation at its core. We help clients envision and build their businesses for the future – running smarter today while adapting for tomorrow’s markets, customers, and communities.
Our multidisciplinary teams specialise in technology strategy and business innovation, digital solutions and applications, and device and systems engineering. We thrive in complex, regulated sectors such as healthcare and finance, connecting strategy, implementation, and operations to help clients build more effective and resilient businesses.

Links:

• Zühlke Website
• Zühlke on LinkedIn
• David Elliman on LinkedIn

We’re excited to announce that Tech Tomorrow will be extending Season 3 into early 2026. Join host David Elliman for more insightful conversations designed to help you navigate the complex world of emerging technology and make more informed decisions as a leader and decision-maker.

You can expect deep dives into topics like AI, cybersecurity, and more.

Be sure to follow the show on your preferred podcast app so that new episodes are delivered to your feed as soon as they’re released.

About Zühlke:

Zühlke is a global transformation partner, with engineering and innovation at its core. We help clients envision and build their businesses for the future – running smarter today while adapting for tomorrow’s markets, customers, and communities.

Our multidisciplinary teams specialise in technology strategy and business innovation, digital solutions and applications, and device and systems engineering. We thrive in complex, regulated sectors such as healthcare and finance, connecting strategy, implementation, and operations to help clients build more effective and resilient businesses.

Links:

• Zühlke Website
• Zühlke on LinkedIn
• David Elliman on LinkedIn

Quantum computing may feel like a distant part of the future, but many experts believe its widespread adoption could arrive sooner than expected. And with it comes a profound challenge: today’s encryption, which protects global cybersecurity, banking, digital identity, and confidential communication, may no longer be secure.

So what happens when quantum computers can break the cryptography that protects our most sensitive information?

In this special Alice in Wonderland-themed episode of Tech Tomorrow, David Elliman speaks with Dr. Sarah McCarthy, Quantum Readiness Programme Lead at Citi, to explore the looming post-quantum era. Together, they discuss what executives, security leaders, and organisations need to understand about quantum risk, how to prepare now, and why waiting may already be too late.

Through playful Wonderland metaphors inspired by Lewis Carroll, including the Red Queen’s race and the Garden of Talking Flowers, David and Sarah explain complex security concepts with clarity and imagination. They outline what quantum computing really is, how modern cryptography works, why cryptographic agility matters, and what could happen if organisations fail to adapt in time. 

The conversation emphasises that leaders must first understand their organisation’s current cryptographic estate, then develop a strategy that allows their systems to adapt and evolve, and finally begin taking practical steps today to ensure readiness well before ‘Q-Day’ arrives.

Episode Highlights

00:34 – Introducing the Wonderland theme and framing the topic.

02:13 – What is quantum cryptography, and why does it matter?

03:5 – How modern cryptography protects everyday digital life.

06:16 – David Through the Looking Glass: Understanding the Red Queen’s Race.

07:23 – Why security strategies must evolve continuously.

09:24 – Cryptographic agility and how leaders can practice it.

11:22 – The urgency behind quantum readiness.

15:49 – David Through the Looking Glass: The Garden of Talking Flowers and digital estate management.

16:32 – Practical, actionable steps executives can take today.

19:59 – What is Q-Day, and when might it arrive?

22:30 – David Through the Looking Glass: The White Rabbit of quantum security.

23:03 – Which companies are making progress in quantum-safe security?

24:38 – Can our secrets survive the quantum leap?

About Zühlke:

Zühlke is a global transformation partner, with engineering and innovation at its core. We help clients envision and build their businesses for the future – running smarter today while adapting for tomorrow’s markets, customers, and communities.

Our multidisciplinary teams specialise in technology strategy and business innovation, digital solutions and applications, and device and systems engineering. We thrive in complex, regulated sectors such as healthcare and finance, connecting strategy, implementation, and operations to help clients build more effective and resilient businesses.

Links:

• Zühlke Website
• Zühlke on LinkedIn
• David Elliman on LinkedIn
• Dr. Sarah McCarthy Website
• Dr. Sarah McCarthy on LinkedIn

As artificial intelligence continues to redefine industries, the question isn’t just what we can build, but what we should. In a world of accelerating automation and algorithmic decision-making, can leaders harness innovation without losing public trust?

In this episode of Tech Tomorrow, David Elliman speaks with Lord Clement-Jones, Liberal Democrat peer, former Chair of the House of Lords AI Select Committee, and co-chair of the All-Party Parliamentary Group on AI. Together, they explore how business leaders can align technological progress with human values and why doing so is not just ethical but essential for sustainable innovation.

They unpack what ‘responsible AI’ really means in practice: from explainability and human oversight to data quality, fairness, and transparent governance. Lord Clement-Jones argues that regulation, far from stifling innovation, can actually enable it by creating the trust, certainty, and accountability businesses need to adopt AI confidently.

The discussion also explores the roles of boards and executive committees, including why AI literacy is now a core competency, how to establish effective oversight mechanisms, and what it means to integrate ethics into AI design rather than retrofit it later. Drawing on his book Living with the Algorithm: Servant or Master?, Lord Clement-Jones reflects on how technology should serve humanity, not the other way around, and why progress must be measured by its benefits to people, not just profit.

Episode Highlights:

01:39 – Introducing Lord Clement-Jones.

03:45 – Why Lord Clement-Jones decided to write Living with the Algorithm: Servant or Master.

06:03 – What is the biggest risk that boards face if they don’t take into account societal responsibility in relation to AI?

07:20 – David’s thoughts: Steps boards and executives can take to ensure they implement useful and trusted AI tools.

08:39 – Defining ethical frameworks in AI.

10:21 – What sort of skill sets do boards need to help them work effectively with AI?

11:31 – What can boards and executive committees do to ensure they are implementing AI tools ethically?

13:25 – The problem with black-box solutions.

15:56 – David’s thoughts: The impossibility of retrofitting responsibility into AI systems.

17:39 – Changing the culture around AI implementation.

20:06 – Why Lord Clement-Jones included the subtitle Servant or Master in his book title.

23:14 – David’s thoughts: The three pillars of responsible AI.

25:26 – The current political landscape and how AI regulation fits into it.

27:16 – Can executives balance AI innovation with societal responsibility?

About Zühlke:

Zühlke is a global transformation partner, with engineering and innovation at its core. We help clients envision and build their businesses for the future – running smarter today while adapting for tomorrow’s markets, customers, and communities.

Our multidisciplinary teams specialise in technology strategy and business innovation, digital solutions and applications, and device and systems engineering. We thrive in complex, regulated sectors such as healthcare and finance, connecting strategy, implementation, and operations to help clients build more effective and resilient businesses.

Links:

• Zühlke Website
• Zühlke on LinkedIn
• David Elliman on LinkedIn
• Lord Clement-Jones Website
• Living with the Algorithm: Servant or Master? AI Governance and Policy for the Future

AI and digital twins are redrawing the boundaries of drug discovery. Once defined by lab benches, animal studies, and years of trial and error, the field is now embracing virtual methodologies that promise faster, safer, and more precise innovation. But could these technologies ever make animal testing obsolete?

In this episode of Tech Tomorrow, David Elliman speaks with Professor Julie Frearson, SVP and Chief Scientific Officer at Charles River Laboratories, about how artificial intelligence is transforming early-stage drug discovery. Julie explains how AI is already accelerating small-molecule design and enabling the use of virtual control animals, reducing the need for live testing without compromising scientific integrity.

They also unpack the growing challenges of explainability, bias, and regulation in AI-driven science. From ensuring transparency and accountability in complex models to understanding how regulators like the FDA are beginning to accept hybrid data sets that combine in vivo results with AI predictions, the discussion balances optimism with realism in a rapidly evolving field.

Ultimately, Professor Julie and David agree that while AI is reshaping discovery, humans must remain firmly in the loop. For now, it is the only way to ensure that innovation remains both ethical, trustworthy, and safe.

Episode Highlights:

01:31 – Areas of drug discovery already transformed by AI and digital twins.

03:25 – Digital twins in animal testing and the creation of “virtual animals.”

05:50 – David’s thoughts: What executives often get wrong about digital twins.

07:30 – How digital twins accurately recreate parts of animals.

10:11 – How regulation currently views AI models in drug discovery.

13:30 – The timeline for regulators to become more comfortable with hybrid data sets.

14:37 – David’s thoughts: How ‘black box’ AI processes create challenges, and how to address them.

16:31 – The role of humans in the drug discovery loop.

17:37 – Will technology outpace regulation?

20:34 – Could AI and digital twins make animal testing in drug discovery obsolete?

About Zühlke:
Zühlke is a global transformation partner, with engineering and innovation at its core. We help clients envision and build their businesses for the future – running smarter today while adapting for tomorrow’s markets, customers, and communities.

Our multidisciplinary teams specialise in technology strategy and business innovation, digital solutions and applications, and device and systems engineering. We thrive in complex, regulated sectors such as healthcare and finance, connecting strategy, implementation, and operations to help clients build more effective and resilient businesses.

Links:

• Zühlke Website
• Zühlke on LinkedIn
• David Elliman on LinkedIn
• Professor Julie Frearson on LinkedIn
• Charles River Laboratories Website