Born to Disrupt – The Future of AI in Business with Tashfin Shafique
- grant6561
- Apr 6
- 3 min read
In this episode of Born to Disrupt, hosts Grant Niven, Simon Hardie, and Mark Walker are joined by Tashfin Shafique, founder and CEO of EMERGEiQ, to explore the real-world application of artificial intelligence (AI) in business. The discussion focuses on moving beyond AI hype, emphasising the need for strong data foundations, ethical deployment, and human-centric strategies as organisations navigate the evolving technology landscape.
AI is Not Magic – It’s Built on Data
Tashfin opens by sharing his background in investment banking and data science, tracing the evolution from legacy systems to today’s AI-driven processes. He stresses that AI is only as good as the data behind it, likening AI to a high-performance car that only runs efficiently with the right fuel (quality data), setup (infrastructure), and driver (human expertise).
Many organisations remain in early stages of AI maturity, often lacking the data infrastructure or strategy needed to realise AI’s potential. Tashfin notes that most companies are still in the "discovery phase", using workshops to understand what AI actually is, what it can do, and what ethical considerations must be addressed.
The Challenge of Data Silos and Strategy Disconnect
A major barrier to effective AI adoption is the siloed nature of business data. Tashfin points out that HR, finance, and IT systems often operate in isolation, creating inconsistencies and making integration difficult. A successful AI strategy must be built on a solid data strategy—normalising, cleaning, and centralising data to enable automation and decision-making at scale.
He recalls examples from his time in banking, including a striking statistic that HSBC once held more data than Google—yet lacked integration across its business units. Today, cloud adoption and strategic partnerships are helping address these gaps, particularly in regions like the Gulf where companies are leapfrogging traditional digital transformation stages.
From Experimentation to Execution
Tashfin distinguishes between theoretical enthusiasm and practical impact. While AI is often treated as a silver bullet, businesses must move cautiously through proof-of-concept phases before scaling solutions. He shares client examples where AI bots reduced headcounts in family offices and private equity firms by automating repetitive tasks like document analysis and number crunching—leading to greater efficiency without compromising quality.
However, success depends on proprietary data and supervised learning. Organisations are increasingly seeking tailored AI models built with their own data rather than relying on open, consumer-grade tools that may present privacy or compliance issues.
Human-Centric AI and the Workforce of the Future
A key theme throughout the episode is the human impact of AI. While automation is reducing the need for certain roles, the discussion acknowledges the inevitable evolution of work—just as spreadsheets once replaced entire rooms of data entry clerks. Rather than replacing people, AI should augment human abilities, enabling workers to focus on creativity, strategy, and empathy.
Still, the hosts question whether enough is being done to prepare the workforce for this shift. Tashfin advocates for continuous learning, up skilling in areas like coding and data science, and engaging younger generations in the ethical use of AI.
The Need for Trust, Transparency, and Regulation
Trust is identified as the foundation for successful AI adoption. With AI still prone to hallucinations and factual errors, Tashfin stresses the importance of managing expectations and offering confidence scores when deploying models. He supports the idea of an ISO-style framework for AI ethics and standards, allowing governments, private organisations, and regulators to collaborate on responsible use.
In sectors like financial services, where trust is paramount, organisations must ensure that AI outputs are monitored and validated. This includes building fail-safes into workflows, maintaining transparency, and ensuring proprietary data is used responsibly.
AI for Good – Real-World Impact
Tashfin shares an inspiring example of AI being used for public safety, such as enhancing women’s safety on public transport through behavioural analysis and facial recognition. This, he argues, reflects the true potential of AI—creating meaningful, human-centred solutions that go beyond profit.
Final Takeaways
Tashfin’s advice for businesses embarking on their AI journey is clear:
Start small – focus on manageable proof-of-concepts.
Educate and upskill teams to understand AI’s risks and rewards.
Be clear about your goals – efficiency, innovation, or expansion – and build your strategy around them.
As the pace of AI innovation accelerates, this episode offers a timely reminder that AI success lies not in the technology itself, but in the people, processes, and principles that guide its use.
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