Generative AI for customer growth

In brief

• We are already seeing a new world made by generative AI running at scale, where businesses are embracing productivity gains today and investing in customer growth.

• Companies that apply generative AI to customer-related initiatives can expect to achieve 25% higher revenue after 5 years than companies focused only on productivity.

• Implementing generative AI gives back through a combinatorial effect—it may finally help close the relevance gap between brands and their customers.

The widening gap between what companies offer and what customers expect has created a “burning platform” moment for marketing, sales and service professionals. Add social and economic pressures, the constant call to do more with less, and it is easy to understand why many are running for cover or wishing for a rewind to 2018.

And if that wasn’t enough to contend with, we now have generative AI entering the fold—at speed.

But here’s the thing: While the hype around generative AI is significant, our work with hundreds of companies is proving that generative AI is indeed unlike any technology in recent times. This is because generative AI impacts every industry, every kind of organization and most of all, people. That means it affects talent and processes, which requires new ways of working and new imperatives like responsibility. Generative AI is different. And this is the point: It’s not just one more layer in the technology stack.

We are already seeing a new world made by generative AI running at scale, where product innovators have real-time visibility into customer service feedback and can shape R&D accordingly. Or where marketers can run incredibly creative campaigns with personalized messages because they know which products are selling to which customers. It’s how supplementing sales and service conversations arrive at the kind of radical solutions that help customers feel that they matter. Insight in one part of the customer value chain informs and powers new insights across the others, enabling businesses to create meaningful connections between businesses and people—at scale. And ultimately, drive business growth.

Unlocking the promise requires that generative AI is treated as a catalyst for reinvention and not just a technology requiring implementation. Seen that way, its potential and place in the reinvention roadmap become clear. Although the risks associated with generative AI are real, the greatest risk may be inaction. Choosing not to act will directly impact not just business productivity today but also future growth trajectory, putting businesses at risk of being left behind.

Generative AI can improve productivity and reinvent for customer growth

We can learn from early movers. Our experience with more than 700 generative AI engagements across all industries and business functions and findings from a global, cross-industry survey of 1,000 business executives reveals how organizations are achieving real growth by applying generative AI to improve productivity. 

Companies taking this approach are making strategic bets on where to apply generative AI to improve customer relevance across the customer organization—from product design and development to marketing, sales and service functions—to create capacity, capability and confidence and seeing tangible value. By using generative AI today to drive profitability, they fuel new possibilities tomorrow, operating at the pace of the customer.

Of businesses using generative AI today, our survey revealed that 90% are focused on using it to improve productivity through automation. This foundation is critical, and it’s one growth path.¹ How companies build on it makes all the difference: We’re also seeing how stronger growth can be achieved by embracing productivity opportunities now and using those to fuel reinvention across the customer organization.

How companies are using generative AI to create customer value

We are already seeing rapid changes in retail, an industry facing structural headwinds. Some of our clients who are working with thin margins are using generative AI to free up resources. That gain is reinvested in operational improvements. For them, an incremental approach is not an option, they need to reinvent so generative AI is core to their strategy—not as proof of concepts but in production, and not just for efficiency but to drive new types of growth through marketing, sales and service.

Early movers like these are reshaping their whole customer value chain, from strategy and products to creative and storytelling. For instance, analysis of our survey results shows that they are 3.7X more likely to use generative AI to identify new and unmet customer needs. By synthesizing huge amounts of customer and market data—doing it with a responsible AI framework and practices in place—they come up with unique insights that they can use to test and develop product concepts. And from our work with clients to date, they are seeing as much as an 80% reduction in data processing time that supports a 40% improvement in speed to market with new products and services.³

Our analysis found that they are 5.6X more likely to believe that generative AI can bring radical innovation to marketing. They are turning creative ideas into global campaigns tailored to individual customers—and doing it cost-efficiently (94% savings in production time) while also solving production and scale challenges (300%–400% increase in content versions).³

It’s not just about speed and productivity. Generative AI can be the catalyst to unlock innovation when paired with human creativity and upholds quality standards—essential ingredients for helping brands differentiate and create authentic human connections.

From promise to reinvention at the pace of the customer

Drawing on experiences from our $3 billion investment in generative AI and work underway on generative AI projects to date, we are seeing some of the biggest opportunities and strongest demand across marketing, sales and customer service. Applying generative AI in areas that add customer value pairs efficiencies with insights that generate innovation.

We have identified five imperatives that companies must address to succeed at reinvention in the age of generative AI. Here is what each means for getting started in the customer organization.

1. Lead with value

When businesses shift from siloed use-cases to prioritizing capabilities across the customer value chain, the customer becomes the heart of the business. A forensic assessment across the organization to identify opportunities for creating more value and relevance for customers will help set priorities.

For example, BBVA has invested heavily in cloud, data and AI to create a more frictionless customer experience. Along the way, the bank has posted record growth in new customers and revenue, as well as improved efficiency and profitability. The bank is continuing to reinvent its business model by building a generative AI–powered financial coach that is designed to disrupt how banks connect with customers.

2. Understand and develop an AI-enabled, secure digital core

The digital core is the engine of customer relevance. It starts with what you already know about customers—first-, second-, and third-party data. It gathers momentum with generative AI, which helps you discover how you can offer customers more meaningful experiences.

Starting from a vision of where customer value can be created will help you get an understanding of what your digital core means for you. This can help contextualize the roadmap for how architecture, technologies, security practices and the generative AI backbone come together in a digital core that will support customer relevance.

3. Reinvent talent and ways of working

In the past year we’ve read a lot about how generative AI is going to impact talent, especially across marketing, sales and service. But generative AI depends on people and how they use it. Wherever automation frees people’s time, it should be seen as an opportunity to reinvest in areas that were once out of reach.

Our research shows that involving people in reimaging how work is done with generative AI can help increase the speed and scale of reinvention by as much as 1.7X and 1.6X respectively.⁴ Creative teams are already experimenting with how to fold generative AI workflows into the creative process. They are developing and becoming versed in prompt engineering and Responsible AI principles and practices. As they learn, they are reinventing the creative process, content production and collaboration.

4. Close the gap on Responsible AI

Generative AI is unique in the way it engages and learns from people, so responsibility and governance are central and must be a first step. Responsibility speaks to the importance of intellectual property, ethics and bias to the customer relationship. When assessed from the perspective of what creates value and customer relevance, the task of adopting responsible AI principles with a clear accountability and governance strategy isn’t simply onerous or about hygiene.

With only 2% of companies reporting that they have operationalized an approach to responsible AI,⁵ this is an opportunity to embrace a wider strategy for differentiation through relevance—specifically by baking into your strategy the values and ethical concerns that people care about such as fairness, trust, equality, and privacy.

5. Drive continuous reinvention

Generative AI can’t be implemented only in pockets of the organization. If marketing, sales and service represents one of the biggest immediate opportunities for generative AI, it is essential that is led by the C-suite, with the board aligned on the vision to create value with and for people.

With a focus on reinvention and enough investment, implementing generative AI gives back through its combinatorial effect. When generative AI applications interconnect, it accelerates and integrates insights and capabilities from across the customer organization, spurring innovation and creating the speed to be able to answer customer needs in real-time, driving growth. 

Bringing it all together

At Accenture, our Marketing and Communications (M+C) organization’s AI-powered transformation looks like a lot of companies’: We are integrating and modernizing our data and implementing platforms that support real-time decision making. To help identify where generative AI would add the most value, we are using AI Navigator, an Accenture proprietary assessment tool that works across functions and industries to help with planning.

We are currently testing and evaluating generative AI across several areas to help accelerate the reinvention of our customer value chain. This starts with getting a data-driven understanding of what is currently driving value for our customers and then using it to identify opportunities for creating future value and efficiently delivering highly personalized experiences.

Our investment in Writer plays a key role in powering our content supply chain. By summarizing and repackaging content, it improves audience engagement through personalization while speeding production and operational efficiency. From our initial 700-person pilot, we saw significant time saved, depending on the use case. We have used the newfound capacity to shift toward driving innovation in marketing using generative AI and being a strategic workforce versus a production workforce.

Because we are a service-based company, our people are our greatest asset. We’re equipping them with generative AI tools that free up their time to focus on the work that matters most. Like our generative AI–proposal developer, which helps our proposal professionals focus more deeply on customizing proposals and solutions to fit our customers’ needs.

All these efforts are expanding the directions our people can grow and changing the roles and skills we need to hire for.

Embracing generative AI isn’t an either-or choice for marketing, sales and service professionals. Inaction now could be the greater risk. The companies we’re working with are already benefitting from higher productivity through generative AI. More important, they are finding new ways to listen and respond to their customers now. There is no better tool to make that happen than generative AI—it’s your bridge to growth through relevance.

About the research

_{Through a survey of 1000 global C-level executives, we investigated how companies are investing in generative AI and related technologies and then modeled the relationship between different investment strategies and expected growth trajectories. The survey fielded in August and September 2023. We supplemented our findings with 30 expert interviews with thought leaders, technology experts, policy specialists and creative professionals.}

Contributors

_{Jen Langusch, Global Generative AI Solution Strategy Lead, Accenture Song}

_{James Temple, Global Generative AI Creative and Design Lead, Accenture Song}

_{Accenture Research: Joshua Bellin, Lead. Contributors: Gaurav Khetan, Konrad Suchecki, Sanjiv Kumar Sharma, James Velasquez}

_{Accenture Song M+C: Guy Norwell, Lead. Contributors: Helen Miller, Nadia Malik, Rachel Jerome}

References

_{¹ Unless otherwise noted, all data comes from the Accenture Generative AI for Customer Growth survey, September 2023.}

_{² Modeling based on the Accenture Generative AI for Customer Growth survey. The difference in growth trajectories was calculated by modeling the growth trajectories of two groups: the 20% of companies that focused most on investing generative AI toward transformative customer-related use cases and the 20% of companies that focused most on productivity use cases.}

_{³Averages and ranges calculated from Accenture Song generative AI projects as of February 1, 2024.}

_{⁴ Accenture Total Enterprise Reinvention Survey (Oct–Nov 2023): n=1,500 CxOs}

_{⁵ Accenture AI CEO survey, August–September 2023}