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Perspectives Edition 29 banner
Edition #29 | November 2023

Accelerating product innovation with generative AI

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Introduction: Higher speeds, higher stakes


The product development process is undergoing a major shift as organizations strive to launch new offerings with all the hallmarks of greatness under tighter cost and time pressures. Many are looking to generative AI (GenAI) to meet these demands, but it’s not always clear how to apply rapidly evolving technology to create products with unique value propositions that foster a sustainable competitive advantage. 


In this issue, Thoughtworks AI experts discuss key GenAI applications across the product development lifecycle, and share the best practices that enable businesses to drive product differentiation and business value with GenAI while avoiding its very real and present risks.


Generative AI adoption in product development set to accelerate through 2032

Source: MarketResearch.biz


Section i. Augmentation along the product development spectrum  


Unlike classic machine learning models, GenAI has the capability to be creative, and can partner with product development teams across all stages of innovation, from synthesizing large amounts of information quickly, to proposing, visualizing and even validating ideas. GenAI applications vary across industries, with those that face less regulatory, IP and privacy constraints having more flexibility and room to experiment.


Photo headshot of Rujia Wang, Head of Customer Experience, Product and Design, Thoughtworks
“GenAI solves the blank page problem that we often encounter at the beginning of the creative process. It expands our thinking on what’s possible by giving us a whole host of ideas to explore and build on.”


Rujia Wang
Head of Customer Experience, Product and Design, Thoughtworks

Section ii. Best practices and principles; balancing the AI and human roles 

Contrary to the oft-held belief that AI adoption requires significant data resources and advanced skills, the barriers to leveraging GenAI for tangible product development gains are lower. The biggest hurdles lie in the human mind, and letting go of established principles and preconceived notions is needed to collaborate with GenAI and produce the best results. Though AI’s presence as a copilot is changing the role of developers and the makeup of product teams, ultimate creative direction – and the associated responsibilities – will rest with humans.


Photo headshot of Farooq Ali, Principal, Product Strategy & Delivery, Thoughtworks
“You have to look at your product development value stream, break it down into where you make key decisions, and then ask yourself the question: Should we be informing this product decision with AI? Should we be augmenting? Or should we be automating? The answers will be different for every company.”


Farooq Ali
Principal, Product Strategy & Delivery, Thoughtworks

Section iii. Avoiding negative consequences


Recognizing GenAI’s flaws and limitations and taking steps to mitigate them are as critical as the need to foster AI fluency. Organizations must identify where guardrails and human intervention are necessary to uphold ethical and compliance standards. On the positive side, while GenAI will create governance problems, it also has the potential to help solve them.


Photo headshot of Zichuan Xiong, Head of Generative AI Product, Thoughtworks
“The governance challenge isn’t governing AI; it’s about governing AI-generated content. The existing operating system to do content reviews, the editorial process – think of compliance, privacy, security, scanning everything – once GenAI adoption goes up, the workload will go up as well.”


Zichuan Xiong
Head of Generative AI Product, Thoughtworks

Section iv. How the use of generative AI will evolve  


As GenAI technologies and organizations’ ability to use them mature, product development roles are likely to converge and drive deeper integration with disciplines such as data science, behavioral economics and even philosophy. Design methodologies will also need to evolve to take AI into account, while models themselves will become more specialized and industry-specific. The reward for enterprises that manage the journey will be the ability to harness more minds and collective creativity in a fast, effective and highly decentralized product decision-making process.


Photo headshot of Farooq Ali, Principal, Product Strategy & Delivery, Thoughtworks
“A lot of product decisions right now are centralized within the product team. We’re already starting to see the decentralization of data, but when you start seeing the decentralization of intelligence [enabled by GenAI], you’re going to see distributed decision-making take place.”


Farooq Ali
Principal, Product Strategy & Delivery, Thoughtworks

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