Perspectives
Introduction: Believe the hype?
Excitement around AI has soared since ChatGPT’s launch, but it is just one facet of a much more fundamental change. The real shift is how AI is maturing to introduce new frontiers of interaction, and unprecedented opportunities for organizations to integrate it into all aspects of the business – while managing the risks that can come with that.
In this issue of Perspectives, Thoughtworks domain specialists explain how to shape strategies for a new age of AI, to nurture a reliable and valuable asset that supports and amplifies human talent, and extends the business’s capacity to grow, innovate and excel.
An appetite for AI knowledge
Source: Deutsche Bank, Google Trends
“We’ll see more and more opportunities as more organizations start to understand what AI might mean for them, and how it can be used to solve problems.”
Ossi Syd
Principal Consultant, Thoughtworks
i. Why an AI strategy is now everyone’s business
Rather than a specific tool, enterprises should see AI as evolving into something like what computers and the internet mean to businesses today: an ubiquitous and critical enabler of value creation. But it can only succeed in that role if it’s made a core element of the organization’s strategy, since it will touch on virtually all processes and functions, as well as the people who power them.
Ensuring this strategy is sound, relevant, and most of all, realistic requires deep alignment between technology and business goals, strong executive sponsorship, and a level-headed assessment of where AI is likely to ease pain points, and produce the most meaningful results.
The elements of a successful AI strategy
“The ability to build or consume solutions isn't necessarily going to be your differentiator – but the ability to integrate them into your processes and products in the best way is.”
David Colls
Director of AI and Data Practice, Thoughtworks
ii. Use cases that deliver outcomes
Data is a vital resource and an optimal avenue for organizations to explore a wide range of AI augmentation possibilities. Keeping systems up to date, reducing labor-intensive manual processes to support complex operations and bringing sources together to deliver insights are all ways organizations' AI investments' are delivering returns in terms of money, time and customer engagement.
But the implications of recent AI developments go beyond productivity and efficiency. It’s becoming increasingly viable to use AI as a creative engine that can scale product innovation and enable decision-makers to step outside their own perspectives, so they make more discerning choices and new ideas come to light.
AI has the potential to address both simple tactical issues and complex strategic challenges
iii. Guardrails and good practices
As AI becomes more sophisticated and ubiquitous, the potential for misuse and abuse is also rising. But organizations can confidently and proactively address these risks by building on the same foundation of ethical practices and clear values that exists in any sustainable enterprise.
By establishing the right – but light – guardrails throughout an AI solution’s lifecycle, from drawing on diverse teams, to taking a test-driven development approach, factoring in a model’s explainability, and designing to enable ‘graceful retirement’ if the need arises, businesses will deliver products that are resilient and reliable in terms of privacy, security and broader societal impact.
Steady rise in AI incidents and controversies reported over the last decade
iv. Guiding the business forward with AI and a skilled human touch
As AI develops, business leaders will be called on to strike a difficult balance between remaining alert to the challenges new solutions may pose, boosting adoption, and leaving room for innovation. With most of these challenges rooted in people as much as technology, getting user buy-in, remaining open-minded as to where interactions between humans and AI should start, and stop, and establishing clear benchmarks for progress will all prevent problems down the road.
Enterprises can also count on some things getting easier, and taking greater strides forward, as AI continues to evolve. Better transparency will address concerns around the explainability and reliability of AI models, while the links between data, engineering and human ingenuity will become even more seamless, lifting systems and people to new levels of performance.
“If you effectively interconnect the strategy with the AI, the data, and the engineering that supports it, you're going to enable people to get value out of data and their daily experiences so they can come up with much better ideas than any individual on their own – and end up with much higher-performing systems.”
Barton Friedland
Principal Advisory Consultant, Thoughtworks
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