Disruption by design: Evolving experiences in the age of generative AI

With unprecedented speed, generative AI has morphed from a media buzzword into a boardroom imperative. More than one-third of organizations have moved past experimentation and are piloting and implementing generative AI across the functions responsible for creating customer experiences, including marketing, sales, commerce, and product and service design.

57% of creative leaders and professionals believe generative AI is the most disruptive force impacting how they will design experiences.

Because organizations see so much potential in generative AI to boost customer satisfaction and scale productivity, they are moving forward rapidly, even as designers wrestle with challenges raised by this game-changing technology. Eight out of ten executives predict the risks associated with generative AI outputs will require more designer involvement. And yet, at the same time, 70% of executives expect generative AI will enable them to do more with fewer designers.

Responding to intense pressure to adopt generative AI, and recognizing the compelling benefits this artificial intelligence technology offers, executives and design teams need to work together on a way forward. This means focusing on where generative AI tools offer the most value, building in data privacy and guardrails to protect the brand, and gaining customer trust.

Generative AI and experiences: The business case for acceleration

Good experience design drives successful business outcomes. Survey respondents who have been recognized for superior product or service design report a 42% higher rate of revenue growth than other organizations. It is not surprising that C-suite executives have set improving customer experience as their top business priority for the next two years.

While this aspiration is not new, gen AI—more than any other recent technology—means organizations may finally achieve their goal of hyper-personalization and accelerated production workflows at scale. Experience design executives say that the transformational benefits coming from gen AI will relieve the pressures that most impact how experiences are designed today.

Where the generative AI bandwagon hits roadblocks

While many business leaders embrace gen AI enthusiastically, practitioners may encounter implementation barriers down the road. Threats to brand safety, intellectual property, and proprietary data top the list. Respondents also worry about data inaccuracies in language models, biases, and uncertain provenance.

However, there is one set of concerns that might make organizations apply the brakes—ethics, bias, trust, and lack of governance. In a recent IBV survey of CEOs, 72% acknowledged they would step back from AI efforts if they thought the benefits could come at an ethical cost. This CEO perspective is interesting when paired with the fact that ethics and empathy rank at the bottom of the list of design strengths respondents expect to be most in demand next year.

Meanwhile, almost one in five (18%) prefer giving employees free rein to use gen AI without direction. This approach could speed AI adoption and encourage next level innovation, but carries significant risk if missteps damage the brand.

Half of organizations say they are establishing an organization-wide approach for governance to manage and monitor generative AI use, but only 5% have put this approach into practice.

Transforming experience design workflows

Despite the risks, many organizational functions responsible for designing experiences across the customer journey are starting to embed generative AI into their workflows.

Customer support, which has a long track record of deploying traditional AI and natural language processing (NLP) to engage individual customers and build customer relationships, is the earliest and most aggressive adopter. 48% of organizations report they are already using generative AI to generate dialogue and answer customer questions for their human agents.

Adoption is coming even faster for those creating customer-facing, text-based chatbots for service agents. Not surprisingly, at 36%, chatbots are one of the most familiar and popular generative AI use cases today. That number soars to 81% less than a year from now.

Using hybrid AI models to deliver the promise of personalization

In every industry, for every customer, the age-old challenge has been to deliver extraordinary, targeted experiences faster and more cost-effectively—affordable personalization at scale. Generative AI systems may finally make these advancements possible, and it is the top reason why most organizations—63%—want to invest in it.

Currently, half the organizations that use generative AI applications access publicly available foundation models such as ChatGPT and DALLE-E. However, what is missing from public models is the hard-won, granular data that companies glean from every employee and customer interaction. Going beyond machine learning, this is the proprietary data that can enable the development of on-brand, hyper-personalized experiences with speed, scale, and specificity. 

Only 24% of organizations are building proprietary models today, but 72% say they will use proprietary models by the end of the year.

Generative AI’s impact on design talent

Easy access to generative AI will likely democratize and streamline many design activities, but the need for top talent will still be paramount. In fact, 82% of executives agree that the risks posed by AI solutions means designers’ project involvement will increase. And almost as many—80%—expect designers will need to play a central role in the creation of generative AI foundation models.

Even though the demand for good designers looks rosy, 70%—the vast majority of executives—also expect that the productivity gains made possible by this AI-driven technology will enable them to do more with fewer designers. Creative managers and designers are less inclined to agree–just 57% think this is likely.

Generative AI will not replace people, but the people who use it will replace those who don’t.

Making progress with DesignOps and managing change

DesignOps-enabled organizations can create procedures for quality control and optimize design systems and guidelines for AI outputs for differentiation and brand safety. They can help ensure designers are properly trained to incorporate generative AI in their workflows, including automation initiatives. And they can define a clear, comprehensive strategy for scaling generative AI into the design of customer journeys and employee experiences—something only a third of organizations have fully implemented.
 

Reducing the stress 

Generative AI addresses the top pressures placed on experience design

Download the report to learn how companies are adopting generative AI in experience design today—and how teams are changing the ways they work to deliver on the promise of AI while avoiding the pitfalls. Then explore an action guide that outlines where executives, creative managers, and content creators can collaborate to make design a catalyst for generative AI transformation.