Building trust in the future of enterprise AI

In recent years we have seen a drastic increase in both the development and implementation of AI across a number of industries, and with pioneering events such as the AI safety summit which took place at Bletchley Park last week, it appears that many of us are eager to join the digital revolution.

However, as with all new technology, there remains a certain amount of scepticism surrounding the advancement of AI, with a few enterprises hesitant to adopt it at scale as they fear it will not be reliable, transparent, or unbiased in production environments.

Speaking with AI magazine, Rajan Padmanabhan, Head of Industry Architecture, Data and Analytics at Infosys, explains why some organisations seem slightly reluctant to adopt AI, even in this digital day and age.

What are the concerns that users have about AI technology?

Padmanabhan explains that there is a notion surrounding the idea that AI is designed to replace humans. “Studies have shown that automation will lead to the redundancy of particular jobs fuelling anxiety around the emergence of AI. However, what the sceptics often miss is the role of AI in augmenting human intelligence as well as enhancing the efficacy of repetitive function. And that development and deployment of AI technology would give rise to new jobs that don’t exist today.”

As well as this, ethical issues and risks of AI deployment raise concerns. “Several AI pilots have revealed flaws such as cognitive biases (for example, racial identification) that sneak into algorithms and models,” says Padmanabhan. “These result in unintended consequences and raise questions around the ethics of using AI as a reliable decision-making tool. Enterprises can overcome such biases by investing in machine learning frameworks and risk-based approaches to develop AI tools.”

As with any new technology, concerns about personal data privacy naturally occur, especially with the risk of AI causing cybercriminals to become more sophisticated. Padmanabhan, who leads architectures, solution strategy, and innovation centred around data, AI, and the cloud, believes: “Given the primacy of data in AI, the access to and use of personal information has been a contentious issue. Additionally, regulators across the globe have introduced strict laws to protect individual privacy, such as the Global Data Protection Rights (GDPR) with the European Union. Such factors have a direct bearing on the adoption of AI at an enterprise level.

What can enterprises do to overcome the scepticism around AI?

In order to overcome the scepticism surrounding the adoption of AI and demonstrate its value, Padmanabhan explains that pilots and case studies could be part of the solution. “According to a survey by the European Commission, 56% of the enterprises in Europe who have deployed AI technologies intend to ramp it up over the following two years, and only 4% intend to scale it down,” he says.

“This is a significant number because it indicates the proportion of enterprises that have overcome inertia and scepticism. Such pilots and demonstrations allow business leaders to make a strong case that goes beyond concept and anecdotal evidence into the realms of evidence and business value which are key to the adoption and successful deployment of AI. 

Padmanabhan also believes that the successful deployment of AI requires several elements to align and be in sync. He says: “Enterprises must develop a customised framework suited for their specific needs and purposes. It is essential to address the issue from two ends. One, adoption of AI among employees which requires them to imbibe a data-driven culture and to upskill associates. Two, the democratisation of technology within the organisation to make it more accessible to employees with the objective of empowering them and decentralising decision-making.”

AI is as much about technology, as it is about human centricity and people

“One of the biggest challenges facing the future of AI is the view that it is a zero-sum game, with only one winner in the end -- humans or machines,” explains Padmanabhan. “And as research and recent developments have shown us, that couldn’t be farther from reality.

Most conversations around AI are centred around data and emerging technologies. This perspective misses out or ignores the human aspects that are equally important for any organisation-wide and transformational intervention such as enterprise AI. For instance, acceptance of AI requires building trust through transparency and buy-in from stakeholders in terms of acceptable use of AI for different purposes.”

Padmanabhan concludes: “Like most path-breaking technologies developed throughout history, what matters isn’t the innovation per se but how we apply it, and AI is no different. At the end of the day, how well enterprises effectively manage AI will determine how much of the US$14tn in gross value they can tap into.”

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