Generative AI is transforming customer growth and productivity by automating personalized content creation, enhancing customer interactions, and streamlining workflows. It enables businesses to scale customer engagement efforts while boosting efficiency, leading to higher satisfaction and faster growth.
Outline :
➢ We are already witnessing a world reshaped by generative AI at scale, where businesses are leveraging productivity gains now while simultaneously investing in customer growth.
➢ By adopting generative AI, businesses benefit from a synergistic effect that can ultimately help bridge the relevance gap between brands and their customers.
➢ Organizations that incorporate generative AI into customer-focused initiatives can anticipate a 25% increase in revenue over five years compared to those concentrating solely on productivity.
Generative AI is increasingly seen as essential for business success, driving significant investments from organizations worldwide. In a recent study, over 2,000 global companies across 15 countries reported plans to spend an average of $47.5 million on generative AI in the current financial year. Additionally, nearly 74% of these businesses consider it crucial or very important to their ongoing success.
But here’s the reality: while the buzz around generative AI is substantial, our experience with hundreds of companies shows that generative AI truly stands apart from recent technologies. It touches every industry, organization, and, most importantly, people. This influence on talent and processes demands new ways of working and introduces key imperatives like responsibility. Generative AI is distinct—it’s not just another layer in the tech stack.
We are already witnessing a world reshaped by generative AI at scale, where product innovators gain real-time insights into customer feedback and can align R&D accordingly. Marketers can launch highly creative, personalized campaigns, knowing exactly which products resonate with specific customers. This integration fuels radical solutions in sales and service, making customers feel valued. Insights from one part of the customer value chain spark new discoveries across others, enabling businesses to forge meaningful connections with people at scale, ultimately driving growth.
Generative AI has the power to boost productivity while transforming strategies for customer growth
We can learn valuable lessons from early adopters. Our experience with over hundreds of generative AI engagements across various topics, coupled with insights from a global survey of various business executives, shows how organizations are driving growth by leveraging generative AI to enhance productivity.
These companies are strategically applying generative AI to improve customer relevance throughout their operations—from product design and marketing to sales and service—boosting capacity, capabilities, and confidence while delivering real value. With 90% of businesses in our survey focusing on automation to drive productivity, this foundation is crucial. However, the key to greater growth lies in leveraging these productivity gains to reinvent the entire customer organization and operate at the pace of evolving customer needs.
How to use generative AI to create customer value
We are witnessing swift transformations in the retail sector, which is grappling with structural challenges. Some of our clients operating with narrow margins are leveraging generative AI to liberate resources, which they then reinvest in operational enhancements. For these clients, taking an incremental approach isn’t viable; they must undergo a fundamental reinvention. As a result, generative AI is integral to their strategy—not merely as proof of concepts but implemented in production, and not just for improving efficiency but also for fostering new growth opportunities in marketing, sales, and service.
Early adopters are transforming their entire customer value chain, from strategy and product development to creative storytelling. Our survey analysis shows they are 3.7 times more likely to use generative AI to uncover new and unmet customer needs. By synthesizing vast amounts of customer and market data within a responsible AI framework, they generate unique insights to test and develop product concepts. From our work with clients, these companies have experienced up to an 80% reduction in data processing time, leading to a 40% faster time-to-market for new products and services.
Our analysis revealed that these companies are 5.6 times more likely to believe that generative AI can drive radical innovation in marketing. They’re transforming creative ideas into global campaigns personalized for individual customers—achieving this with 94% savings in production time. At the same time, they are overcoming production and scaling challenges, seeing a 300% to 400% increase in content variations.
Strategies to drive generative AI success for productivity and growth
The challenge moving forward is to fully leverage the factors that can fuel generative AI success while overcoming potential barriers. Here are three key actions businesses can take to maximize returns from generative AI adoption:
1. Ramp Up a New Talent Strategy: Talent remains the top challenge for generative AI adoption. Concerns about the cost and availability of skilled workers in the market, as well as underdeveloped internal talent strategies, are common. While 54% of businesses plan to implement role-specific upskilling programs, only 25% are considering organization-wide training. To create a robust generative AI retraining program, companies need to carefully assess the technology’s impact on various roles, tasks, and skills across their workforce and develop a strategy that includes the majority of their talent base.
2. Shore Up Consumer Trust: Building trust requires businesses to establish clear ethical guidelines for AI use and maintain transparency about their AI models, including how data is used and the safeguards in place to mitigate risks. Leaders should also take a cautious, measured approach to AI experimentation to minimize or quickly reverse any negative effects while ensuring innovations are commercially viable. This approach will allow businesses to adapt based on feedback, fostering positive consumer perception.
3. Boost Technology Infrastructure and Operational Agility: As generative AI solutions mature, businesses must ensure their internal technology infrastructure is ready to handle AI workloads. Currently, only one-third of respondents feel their infrastructure is mature enough. Leaders must strengthen IT systems by investing in cloud computing, high-performance data storage, and robust data governance to ensure quality and accessibility. Additionally, adopting agile methodologies like MLOps will facilitate continuous development and adaptation, while cross-functional collaboration will ensure seamless integration of AI across business functions.
By focusing on talent, trust, and technology, businesses can position themselves for generative AI success and drive meaningful growth.