Generative AI represents a paradigm shift in how organisations will operate, offering unprecedented opportunities for innovation and growth. To explore this further and to understand the business priorities and challenges on the AI agenda, Expleo hosted an AI & Wine roundtable event for technology and transformation leaders at the historical Sandeman’s Quarter on the 9th of May 2024.
Here are the five key takeaways from the discussion:
1) AI process development
Our speakers made the connection between AI, which is at the cutting edge of innovation, and the creation of wine which is an ancient manual trade. By approaching AI in a similar way to wine production, they emphasised the importance of starting with the manual processes and having the right roots in place – how did you do it the first time round and then how did you digitise and accelerate?
But with the AI gold rush underway, we should not underestimate the importance of implementing controls and security around AI which are essential in deploying new tech. Although developing at an incredible pace, AI is still a new technology and organisations need to consider good business practices of risk management, cyber security, data quality and control.
2) Critical considerations and the importance of quality
AI is the biggest technical innovation of the era, and it’s scary but exciting at the same time. They urged organisations to approach AI implementation thoughtfully by asking the right questions and understanding the purpose. AI must add tangible value to businesses so make sure you’re not just knee jerking or wasting resources. Know what you are trying to solve before experimenting with generative AI.
Ensure you have the right spread of data and that the data is fit for purpose – ask yourself: is the quality there? Historically many organisations have rushed into AI production, but it’s inefficient and quite restrictive. We advocate a more strategic approach, emphasising the opportunities to unlock groundbreaking solutions if you combine AI quality assurance with data correctly.
3) Significance of synthetic data
Governance, privacy and accountability issues are challenges that organisations face in AI adoption. Synthetic data emerged as a solution to address data scarcity and privacy concerns, enabling organisations to augment real-world data with artificially generated data. This approach accelerates AI development while improving the robustness and reliability of the AI. Leveraging synthetic data is a game changer within AI but you need to ensure the quality is there.
Synthetic data and quality insurance combined are an indispensable pillar of successful AI adoption. It brings synergy, optimisation and trust, but it’s vital to approach it in the right manner.
4) Generative AI and human oversight
Generative AI is not only possible but essential. We are seeing paradigm shifts in AI, especially around unstructured data. No longer is it about having the right answers but more about asking the right questions. And you still need a human in the loop. There is a recognition that human input is extremely important for the successful adoption of AI as generative AI is far from perfect in its current form. AI is a tool, and we need to learn how to master it to realise the true benefits.
As well as having the potential to revolutionise operations, generative AI is posing some interesting questions for how the future works. While AI is a game changer, human behaviour (what we do and how we act) hasn’t changed.
5) The future of AI
Now that CEOs can now get their hands on the technology, they can lead from the front. Long, costly transformations may be a thing of the past but human behaviour hasn‘t changed. The big risk is that generative AI is a solution looking for a problem. Technology, and how we use it, mustn’t create more problems than it solves. Having the right processes and data in place at the start of your AI journey is key.
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