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EngineeringBeat: GenAI and cloud for consumer products
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Cloud and GenAI solutions are increasingly crucial to digital transformation in the consumer products (CP) industry. In this edition of EngineeringBeat, we offer five key insights that CP organizations can use to boost their cloud and GenAI capabilities and gain more value from their transformation.
Generative AI is the future. Build the right foundation to harness its power.
Customers, culture, talent, and everything in between is fair game for feeling the impact of generative artificial intelligence. Consumer products companies will use it to gain new customers and build better relationships with current ones, which will lead to amazing growth opportunities. They’ll also tap Generative AI to build next-gen talent pools that fuel their ability to innovate and outpace their competition. In fact, recent Deloitte research indicates that 62% of CP companies are already making investments in AI/machine learning, a number which is almost certain to rapidly increase over the coming year.
However, Generative AI will bring changes in cloud architecture. With the large language models (LLMs) Generative AI uses, data storage and scalability become more critical than ever as data volumes will increase almost exponentially. Rethinking security is also essential because the sensitive information contained in LLMs will necessitate stricter access and egress controls over data. AIOps—which helps match needs to resource utilization—will also be key so that budgets and operations can be optimized.
Learn more about how Generative AI will change cloud architecture: Listen to the OnCloud podcast.
Cloud is the foundation for Generative AI. Build a modernization strategy.
Cloud is the foundation for Generative AI. With cloud-based Generative AI’s LLMs, CP organizations can more quickly make sense of their customer data—in context—to develop and prototype new products and get those new products to market faster. They can also use AI-powered analytics to get faster, more meaningful insights into their data to build deeper, tailored relationships with their customers. Deloitte’s research shows that a majority of CP organizations are doing just that. In fact, 68% are investing in cloud platforms to modernize their tech stack, and 89% are investing in advanced analytics to gain better insights.
But modernization isn’t easy. It requires a thoughtful, intentional approach that focuses on optimizing the value that cloud returns to the business. Consumer products companies can modernize by first developing a strategy that focuses on their unique needs and the path to meet those needs. It’s also essential to use cloud-native, modern software engineering principles to design a cloud-based ecosystem that’s flexible, scalable, and secure to support the ongoing journey of business and digital transformation.
Learn more about cloud native software engineering: Watch the video
Customer relationships are paramount. Go from big to small with cloud and Generative AI to craft a personalized approach.
Customer behavior is constantly changing, and those customers are increasingly demanding personalization. Consumers want to know they’re unique, and they want companies to speak directly to them with meaningful, personalized offers. In fact, recent Deloitte research found that 69% of consumers say that they’re more likely to buy from a brand that offers a personalized experience. Cloud and Generative AI can enable that, with cloud providing the computing and storage power and Generative AI the ability to gain insights into customer data to generate offers at the individual customer level.
The path to personalization starts with a move from big to small. Instead of brand-centric strategies, CP organizations can move to a customer-centered strategy, with an agile culture that replaces command and control structures. They can also replace ERP-centric talent models and recruiting methods with a move to recruit and retain digitally fluent talent who can learn and grow with the organization.
Tech talent is the heart of the modernization journey. Nurture your relationship with your tech team.
Tech talent is at a premium, and CP organizations are realizing that their talent pool is a critical lever to drive cloud value. With the competition for talent, worker satisfaction is a top goal. A recent Deloitte survey found that 54% of respondents said they were motivated by the work they would do in a given role, while traditional motivators such as benefits and compensation are less important.
To nurture tech talent, it’s essential to find novel ways of recruiting the right people to the right roles and increasing employee satisfaction to help them grow and to retain them long term. Reimagining the corporate culture to be more diverse and inclusive is the first step. Understanding and encouraging modern ways of working—remote, hybrid, autonomous teams—is the next. Finally, it’s also crucial to build a culture of innovation where everyone is heard and encouraged to think big and follow their passion.
Learn how to more effectively nurture your tech talent: Read the Technology Skills Insights report
To optimize cloud value, don’t just spend. Invest the right way.
For many CP organizations there’s a value gap in their cloud implementations. Recent research by Deloitte suggests that fewer than 50% of CP companies report seeing the value they expected from their cloud investments, and only 35% say they are seeing promised innovation capabilities. Closing this value gap will be crucial to success for CP companies as markets and customer demands evolve. CP companies will need to leverage cloud, Generative AI, and other digital technologies as a force multiplier to innovate and differentiate.
Strategy plays a key role in cloud and Generative AI investment decisions. That strategy must be holistic and involve all aspects of the business, not just technology. It’s also essential to develop a standardized approach to modernization and migration and establish core cloud and Generative AI components, security, and governance. Finally, and perhaps most importantly, it’s crucial to have a program in place to manage transformation efforts long term to ensure that cloud and Generative AI implementations remain optimized as needs and markets change.
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