Despite the current absence of a cohesive regulatory framework, research from the digital services firm Emergn has found that artificial intelligence (AI) will play a significant role in the future of digital products and services. 

The conclusion was gleaned from a survey of over 400 respondents from both the US and UK. Of the respondents, 28% were business leaders from companies with an annual revenue of $100-$999 million, 51% with an annual revenue of $1-$4.9 billion, and 21% had over $5bn. 

It found that above the overwhelming 94% of new products and services projected to incorporate AI in their development process, 75% of leaders considered AI critical to reshaping their sector and product development cycles over the next three years.

Along with the enthusiasm, there was also a stark agreement on the considerable work that lies ahead to ensure the adoption of AI translates into improved productivity, efficiency, and accessibility.

Notably, 71% of respondents emphasised the need to address ongoing challenges related to data privacy, 70% focused on ensuring AI accuracy, and 60% highlighted concerns about the scalability of AI solutions.

The application of AI in product and service development could have significant societal implications. From perpetuating existing biases, to failing to safeguard data, the potential risk involved is multifaceted. 

According to an AI model transparency index produced by Stanford University, the top five most transparent AI models (Llama2, BLOOMZ, GPT-4, Stable Diffusion 2, and PaLM2) scored between 40%-54%, when the researchers at Stanford say companies should score for a score over 80%. 

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This points to the fact that in tandem with minimal regulatory guardrails currently in place, many AI models themselves are below par in terms of transparency. 

“AI offers a tremendous opportunity to create more useful products that deliver better experiences, more efficiently. However, it’s true value lies in its application,” said Alex Adamopoulos, Emergn CEO.

“To use it best, organizations must be building their product in the right way. This requires organizations to really understand what their customers care about and then have in place appropriate structures to oversee the use of AI, particularly the data on which it is trained, to develop and test the product.”