Podcast Summary: Born to Disrupt – The Future of AI in Business with Tashfin Shafique
In this episode of Born to Disrupt, hosts Grant Niven, Simon Hardie, and Mark Walker welcome Tashfin Shafique, founder and CEO of EMERGEiQ, to explore the practical application of artificial intelligence (AI) in business. The conversation dives into how organisations can move beyond the buzzwords, embracing data, strategy, and ethics to unlock meaningful and sustainable value from AI technologies.
From Banking to AI Innovation
Tashfin begins by outlining his background, which spans over two decades in investment banking, where he worked with data and technology long before the AI revolution took hold. He reflects on how data management has evolved—from manual entry and spreadsheets to advanced AI and automation tools. This evolution has culminated in the rise of generative AI, which he refers to as the latest "buzzword," yet one that holds genuine potential if deployed correctly.
The Importance of Data Foundations
A core message throughout the episode is that AI is only as effective as the data behind it. Tashfin compares AI to a high-performance car—it requires the right fuel (data), engineering (infrastructure), and driver (human oversight) to function optimally. Despite the AI hype, many organisations remain at the early stages of adoption, lacking clean, structured, and integrated data systems. Without fixing these foundational issues, attempts to use AI will fall short.
The hosts discuss how many businesses, especially in banking, have historically struggled with data silos, where departments such as HR, finance, and IT hold disconnected data that cannot be used cohesively. Tashfin reinforces that a robust data strategy must come before an AI strategy, and the two should be integrated to maximise effectiveness.
AI in Practice – Use Cases and Efficiency Gains
The conversation shifts to tangible examples of how AI is delivering real business outcomes. Tashfin shares how private equity firms and family offices are now leveraging AI to automate data-intensive tasks—such as processing decades of contracts, legal memos, and filings—using proprietary models trained on their own data. These tools enable companies to build knowledge centres and internal chatbots, allowing them to extract key information quickly and accurately.
One example discussed involved a family office that reduced its analyst team from four to one by implementing AI bots capable of managing most data analysis functions. Far from merely cutting costs, this approach freed up human resources for higher-value work, demonstrating how AI can streamline operations without undermining strategic capabilities.
Human-Centred Design and Ethical Considerations
A major theme of the episode is the importance of maintaining a human-centred approach to AI. While AI offers efficiency gains, the hosts caution against ignoring the social and ethical implications of automation. Tashfin emphasises that AI should augment—not replace—human roles. For instance, in ESG reporting, AI can flag anomalies and summarise trends, but human judgement remains essential for interpretation and decision-making.
The panel discusses the risk of widespread job displacement and the importance of upskilling the workforce. Tashfin advocates for continuous learning, suggesting that individuals—especially young professionals—must adapt by developing skills in coding, data science, and AI ethics to remain relevant in a changing job market.
Regulation, Trust, and the Role of Standards
Trust emerged as a crucial factor in AI adoption. Tashfin notes that while AI can provide 80–90% accuracy, it is rarely flawless. Organisations must build confidence levels into AI outputs, particularly during the proof-of-concept stage. The hosts debate the need for an international AI standards body, akin to ISO, to guide responsible use and address ethical concerns, especially in industries such as finance, where public trust is vital.
Tashfin explains that his firm embeds fail-safes and supervision in every AI deployment, particularly when handling sensitive or proprietary data. By continuously monitoring and educating clients, emergeIQ aims to build trust in AI systems that are not only effective but transparent and accountable.
AI for Good – Purpose Beyond Profit
The episode concludes on a positive note, with Tashfin sharing an inspiring example of AI being used to enhance women’s safety on public transport through behavioural analysis. He argues that such applications, which prioritise social impact over commercial gain, represent the most exciting potential for AI—technology deployed for good.
Ultimately, this episode presents a balanced view of AI: full of potential, but reliant on good data, thoughtful strategy, ethical oversight, and above all, human guidance.
