Emerging Technologies

The could versus should debate: aligning AI with what consumers want

An image of a man paying with a phone, illustrating the use of AI

People have different expectations of how they should transact with AI Image: Photo by Clay Banks on Unsplash

Ravi Kumar S.
Chief Executive Officer, Cognizant
Oliver O’Donoghue
Head of Research, Cognizant
This article is part of: World Economic Forum Annual Meeting
  • There is polarization among consumers regarding AI adoption; 'accelerators' welcome the technology in their purchase journey, while 'anchors' resist it.
  • Yet, even accelerators demand human involvement at key moments of their buying journey.
  • We must thoughtfully navigate the line between what could be automated and what should be, to ensure that technology and people work together for a better future.

By unlocking unprecedented productivity gains, AI has turned business upside down. Workforce shifts are a massive component of these gains. As Cognizant's New work, new world study projected last year, 90% of jobs will be affected by AI, most of them dramatically. Myriad roles that impact the customer experience could be automated: service reps, financial advisors, claims adjudicators and more.

But AI is roiling the consumer world too. Cognizant's latest report, New minds, new markets, depicts a fragmented market that will challenge business leaders balancing bottom-line productivity against human involvement. The study reveals polarization among consumers regarding AI adoption; 'accelerators' aggressively incorporate the technology in their purchase journey, while 'anchors' resist AI with every fibre of their being. Anchors hold plenty of economic power today, but it’s shrinking. Meanwhile, accelerators will control 30% to 55% of purchasing power by 2030.

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But, while consumer demand for AI-enabled products will increase, leaders should be wary of over-indexing on productivity gains. The most enthusiastic accelerators still demand human involvement at key moments of their buying journey, even when AI could offer faster or more accurate outcomes.

Why is this the case? Two key factors emerged:

1. The stage of the purchasing journey matters. Many consumers are comfortable using AI to discover and shortlist products, but fewer would let it control their transactions. This preference intensifies with higher stakes purchases, such as healthcare or financial investments.

2. People don’t unilaterally trust AI systems to make the right decisions on their behalf. Almost half of those who won’t use AI to learn about or purchase products cite a lack of trust in the technology’s accuracy, completeness, intent or underlying data security.

For businesses, factoring these critical dimensions into the AI strategy is vital, even existential. Companies that view AI solely through the narrow lens of productivity and headcount do so at their peril.

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    Age is a factor—but not the only factor

    People’s age plays a role in their attitude towards AI. But it’s far from the only factor; personal finances, education and whether they have a young family all have an impact. In most cases, the differences between cohorts are subtle and surprising. Businesses must take this into consideration when forming an AI strategy.

    For instance, only 3% of survey respondents aged 55 and older would let AI purchase diagnostic healthcare services on their behalf. For those aged 25 to 34, that number rockets to 20%. In a vacuum, this differential might prompt healthcare providers to focus on the younger cohort. But that would be a mistake: we found that in another component of the customer journey— learning about these services — older consumers come reasonably close to their youthful counterparts (19% to 28%) in their willingness to use AI.

    To appeal to both groups, businesses should focus on a blended approach, enabling AI-driven discovery while ensuring a seamless transition to human interaction for decision-making and service delivery.

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    An adaptable strategy is needed for navigating AI

    Organizations must navigate evolving AI expectations with care. To succeed, businesses should incorporate the following into their strategy:

    Beware a slow take-off on a short runway

    Our research indicates that early adopters will quickly exert pressure on businesses by demanding AI integration into their operations or favouring AI-native companies. The pressure will increase as early adopters become a more significant economic force, giving businesses limited time to prepare. Companies that eliminate friction and deliver effective customer experiences across a range of modalities will capture consumers keen on AI — without alienating those who’d rather do without it.

    Focus automation efforts where customer value and productivity align

    Companies seeking to transform their business models through productivity gains should — as long as they are creating value for customers. For example, content development roles, which are highly exposed to automation, can be augmented with generative AI tools to create hyper-productive writers and designers. This also presents an opportunity for personalized marketing that better serves customers who are currently frustrated when they don’t understand how products and services meet their needs.

    Design multi-modal workflows blending human and AI interactions

    As our research demonstrates, attitudes towards AI are complex and varied. To account for this, businesses must integrate humans and 'bots into workflow processes to ensure a seamless user experience. For instance, in financial services, clients may initially explore investment options with a chatbot or voice assistant — only to balk at finalizing such a major transaction with AI alone. These consumers must be transitioned to a human advisor who has immediate access to AI-driven insights regarding their profile and needs. Anywhere humans play a customer-facing role, they should be armed with AI tools that help them turn interactions into 'moments that matter.'

    Emphasize human responsibility to reinforce trust and accountability

    One finding from our research is that many consumers trust people more than they do AI. Even the most bullish air concerns about the technology’s data security, completeness and accuracy. They also worry about the true motivations of the technology — and its designers. Organizations must make it clear that a human is in the loop and is ultimately accountable for the outcome and be ready to provide explanations and context or even take over the process entirely.

    The balance between automation and the human touch isn’t just a technological challenge — it’s a leadership opportunity. Organizations must listen carefully to customers, design adaptable strategies and empower their workforce to thrive.

    Trust will remain the cornerstone of these efforts. By combining AI’s potential for efficiency with human oversight, businesses can build stronger connections with consumers, deliver value and foster confidence in their brands. For leaders, the imperative is clear: thoughtfully navigate the line between what could be automated and what should be, ensuring that technology and people work together to shape a better future.

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