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AI Strategies for the Modern Enterprise

In a wide range of sectors, including telecommunications, consumer packaged goods (CPG), banking, healthcare and energy, enterprise leaders are significantly ramping up their investment in artificial intelligence (AI), with a projected fivefold increase in spending in 2024. Their drive to harness AI for enhanced efficiency, improved personalization and reduced operational costs is no longer approached with trepidation; rather, it is now pursued with a sense of urgency.

This study by venture firm Andreessen Horowitz found that: “Over the past couple of months, we’ve spoken with dozens of Fortune 500 and top enterprise leaders, and surveyed 70 more, to understand how they’re using, buying and budgeting for generative AI. We were shocked by how significantly the resourcing and attitudes toward genAI had changed over the last six months. Although these leaders still have some reservations about deploying generative AI, they’re also nearly tripling their budgets, expanding the number of use cases that are deployed on smaller open-source models and transitioning more workloads from early experimentation into production.”

“We were shocked by how significantly the resourcing and attitudes toward genAI had changed over the last six months. – Andreessen Horowitz”

Several key factors are compelling enterprise leaders to markedly increase their investments in AI for 2024. These include enhancing data security, streamlining process automation and improving customer care through AI deployment. Furthermore, the availability of domain-specific AI, tailored for particular use cases and applications, is accelerating this trend. For instance, OpenAI recently broadened its offering with a custom model training program designed to assist enterprises in deploying personalized, domain-specific solutions.

An illustrative example of this is how OpenAI’s custom-trained models have enabled SK Telecom, a leading Korean telecommunications company, to refine its customer service conversations in Korean. Similarly, the AI-powered legal platform, Harvey, has collaborated with OpenAI to develop a custom model specifically for navigating case law. These examples underscore the pivotal role of tailored AI in enhancing operational efficiency and customer engagement across the telecommunication and legal sectors.

A New Era of Digital Transformation

Digital transformation, defined as the integration of digital technology into all areas of a business to fundamentally change its operations and customer value delivery, is being increasingly driven by AI.

Organizations have recognized that AI’s role extends beyond merely facilitating writing and image and video creation; custom AI models offer a competitive edge, tailored to enhance operations and deliver personalized marketing experiences. Consider the example of Kellanova, a CPG brand spun off from Kellogg’s, and its use of AI and Machine Learning: “Machine learning algorithms help us analyze vast amounts of data to optimize inventory management, demand forecasting and production planning. We are also using generative AI to enhance customer engagement through personalized recommendations based on consumer behavior and preferences.”

“This transition is not just about adapting to digitalization; it’s about revolutionizing customer experiences, product offerings and market strategies. Redefining consumption, production and customer relationships in profound ways.”

Furthermore, Kellanova leverages these advanced platforms to boost employee collaboration and create personalized marketing offers, driving e-commerce conversions and sales. The transformative power of AI, as articulated in the article, extends beyond the CPG industry: “This transition is not just about adapting to digitalization; it’s about revolutionizing customer experiences, product offerings and market strategies. In this age of transformed CPG digital, the company is charting a course through uncharted territory, redefining consumption, production and customer relationships in profound ways.” This statement underscores the expansive impact of AI across various sectors, heralding a new era of digital transformation.

How Is Enterprise Using AI?

The Andreessen Horowitz study highlights that while enterprises are enthusiastic about AI’s potential to address internal business challenges, there remains a degree of caution when it comes to customer-facing solutions. This caution stems from concerns that AI-generated responses might be inaccurate or present safety risks, potentially leading to public relations issues, especially in privacy-sensitive consumer sectors.

An example provided in the study involves Air Canada’s AI chatbot, which led to a customer service mishap: “The passenger claimed to have been misled on the airline’s rules for bereavement fares when the chatbot hallucinated an answer inconsistent with airline policy.” Despite these challenges, the study also illustrates that AI’s strengths in text summarization and knowledge management are increasingly being leveraged within enterprises, showcasing a growing confidence in AI for internal applications.

Andreessen Horowitz_Chart

When it comes to simplifying workflows or eliminating redundant and time-consuming tasks,“78% of customer service professionals say AI and automation tools help them spend time on more important aspects of their role.” Here are some additional use cases of how enterprise is integrating AI across both consumer brands and B2B sectors:

Improving Call Center Operations:

Handling over 11,000 calls a day, HomeServe relies on its AI virtual assistant, Charlie, to immediately answer customer questions, initiate the claims process and schedule repair appointments.

Prioritization of Inbound Emails

Guardian Lemon Law, a California law firm, has implemented a Natural Language Processing (NLP) tool to sift through their massive email influx, prioritizing messages that require immediate attention. Leveraging ChatGPT’s language analysis features, this AI adoption has notably enhanced the firm’s productivity, resulting in a 12% increase in signed cases, which indicates improved customer satisfaction.

Voice AI in Banking:

Axis Bank offers AI-powered voice banking via Alexa devices for a range of requests, demonstrating AI’s potential to reduce call center traffic and improve customer self-service

24/7 Digital Concierge:

GWYN (“Gifts When You Need”), a concierge service launched by 1-800-Flowers.com, allows customers to engage in conversation on the company’s desktop and mobile websites to find and order the perfect bouquet or gift basket. GWYN offers a more intuitive shopping experience by asking users about their desired purpose or occasion in order to tailor product suggestions, thus eliminating traditional form-based selection searches.

Business Operations:

As the leader in luxury fashion, Louis Vuitton is pioneering the use of AI in its operations, particularly in inventory management and demand forecasting, ensuring that its exclusive products are available precisely when and where its customers need them.

Preparing for the Next Wave of AI Innovation

As AI continues to evolve at a rapid pace, it’s imperative for enterprise leaders to stay informed about future trends and the potential impacts of AI innovation, not only within their own sector, but also in adjacent ones. My advice for all leadership roles—not solely the CIO—is to actively keep abreast of AI developments. Often, looking beyond one’s industry can yield significant inspiration and valuable insights. Consider identifying your most pressing challenges and discerning which can be incrementally addressed rather than seeking an all-encompassing solution. This approach allows for a systematic exploration of AI advancements that align strategically and securely with your enterprise’s business objectives.

Questions? Please email me here. As always, thank you for reading.

Photo by Shubham Dhage on Unsplash