Leading Off: What to do about generative AI right now: A leaders guide

In an evolving software-driven landscape, many companies are already taking steps to transform their go-to-market (GTM) strategies by using tech to increase the functionality of their core offering and drive higher engagement with customers. Take the retail apparel industry, where fashion houses and mass retailers alike are expanding physical runway shows and stores into the virtual world with interactive experiences, gamified content, and new ways to generate awareness and monetize merchandise. For example, Gucci launched metaverse fashion exhibits that mirror physical ones,12“The Gucci garden experience lands on Roblox,” Roblox, May 17, 2021. Gap opened in-game storefronts with digital replicas of merchandise and fashion mini-games13“Gap launches first virtual experience on Club Roblox to empower teens with the freedom to be yourself,” Gap, May 20, 2022. And has launched virtual dressing rooms, and Tiffany & Co. raised $12.5 million through the instant sellout of its NFT drops in conjunction with new-product launches.14Jacob Oliver, “Tiffany & Co. Technical skills are mere table stakes for a role as complex and multifaceted as product management.

The unmanageably huge volume and complexity of data (unmanageable by humans, anyway) that is now being generated has increased the potential of machine learning, as well as the need for it. Automation has taken a leap forward with the recent introduction of generative AI tools. “Generative” refers to the fact that these tools can identify patterns across enormous sets of data and generate new content—an ability that has often been considered uniquely human.

Responses show many organizations not yet addressing potential risks from gen AI

The metrics are whether respondents “felt happy,” were “Able to focus on satisfying and meaningful work,” and were “in a flow state.” In all cases, the more positive responses were, on average, doubled among those using generative AI. In this visual Explainer, we’ve compiled all the answers we have so far—in 15 McKinsey charts. We expect this space to evolve rapidly and will continue to roll out our research as that happens.

Kweilin Ellingrud is a senior partner and director of the McKinsey Global Institute and is based in Minneapolis. Asutosh Padhi is McKinsey & Company’s North America managing partner and is based in Chicago. What sets this partnership apart is its focus on creating Yakov Livshits a seamless experience for companies from start to finish. With 40 percent of enterprises planning to invest in this kind of AI, the collaboration between Salesforce and McKinsey could be a game-changer for many businesses, helping them achieve measurable results.

The future is now

For one, it’s crucial to carefully select the initial data used to train these models to avoid including toxic or biased content. Next, rather than employing an off-the-shelf generative AI model, organizations could consider using smaller, specialized models. Organizations with more resources could also customize a general model based on their own data to fit their needs and minimize biases. Many initiatives are in place, but it will be critical to dramatically scale up what works and take a proactive approach to filling key shortages. One promising solution, still in the early stages, involves digital learning and employment records—a kind of digital microcredential that can document how an individual worker has acquired skills and also translate across companies and over time.

Whether you want to kick off a long-overdue digital transformation or jump-start an underperforming business unit, you may need to incorporate gen AI as an essential component. This may include public data scraped from Wikipedia, government sites, social media, and books, as well as private data from large databases. OpenAI, for example, partnered with Shutterstock to train its image model on Shutterstock’s proprietary images.8“Shutterstock partners with OpenAI and leads the way to bring AI-generated content to all,” Shutterstock, October 25, 2022. To that end, we recommend convening a cross-functional group of the company’s leaders (for example, representing data science, engineering, legal, cybersecurity, marketing, design, and other business functions). Such a group can not only help identify and prioritize the highest-value use cases but also enable coordinated and safe implementation across the organization.

And automation of knowledge work is now in sight

Yakov Livshits
Founder of the DevEducation project
A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.

OpenAI hasn’t released exact costs, but estimates indicate that GPT-3 was trained on around 45 terabytes of text data—that’s about one million feet of bookshelf space, or a quarter of the entire Library of Congress—at an estimated cost of several million dollars. Overall, we expect more growth in demand for jobs requiring higher levels of education and skills, plus declines in roles that typically do not require college degrees (Exhibit 5). Labor supply may continue to be constrained, given that one in four Americans will be of retirement age or older by 2030. Without higher participation rates, increased immigration, or meaningful productivity growth, labor shortages could be a lasting issue as the economy and the population grow.

This is in contrast to most other AI techniques where the AI model attempts to solve a problem which has a single answer (e.g. a classification or prediction problem). The report also revealed that gen AI is not just a fleeting trend but a strategic focus for many organizations. Nearly half (40%) of those reporting AI adoption indicated that their companies plan to ramp up their overall AI investments, thanks to gen AI.

Work and productivity implications

Lego partnered with Epic Games to create a metaverse for kids to connect, playing between digital and physical worlds seamlessly. And L’Oréal invested in Digital Village—a virtual world-building platform and nonfungible token (NFT) marketplace—to bet on opportunities within the metaverse and Web3 for virtual store creation. Salesforce and McKinsey’s collaboration creates a new end-to-end experience for companies that links a company’s business strategy to AI use cases. This Yakov Livshits is followed by McKinsey’s rapid solution design with a proof of concept, MVP build and the ability to test solutions with users to connect AI products and people systems for full scale roll out. For closed-source models in which the source code is not made available to the public, the developer of the foundation model typically serves as a model hub. Sometimes the provider will also deliver MLOps capabilities so the model can be tuned and deployed in different applications.

To streamline processes, generative AI could automate key functions such as customer service, marketing and sales, and inventory and supply chain management. Technology has played an essential role in the retail and CPG industries for decades. Traditional AI and advanced analytics solutions have helped companies manage vast pools of data across large numbers of SKUs, expansive supply chain and warehousing networks, and complex product categories such as consumables. In addition, the industries are heavily customer facing, which offers opportunities for generative AI to complement previously existing artificial intelligence. For example, generative AI’s ability to personalize offerings could optimize marketing and sales activities already handled by existing AI solutions.

Overall employment in low- and middle-wage occupations has fallen from prepandemic levels, while occupations that pay more than $57,000 annually added about 3.5 million jobs. However, it is unclear how many higher-paying roles were filled by people who moved up and how many were filled by new entrants to the labor force. Demand for lower-wage service work remains, but fewer workers are accepting these roles.

• Technical skills are mere table stakes for a role as complex and multifaceted as product management.
• Is likely to change work activities substantially, particularly in healthcare, STEM, and professional services.
• Many retail and consumer players recognize this reality and have already made decisive software and technology investments.
• This erosion comes after an extended 20-year trend of steadily falling participation.
• The McKinsey Global Institute began analyzing the impact of technological automation of work activities and modeling scenarios of adoption in 2017.
• So far, North America-based respondents lead the globe in terms of gen AI adoption for work, with 28% of them using the tech in their jobs and outside of work, compared to 24% of European respondents and 22% of Asia-Pacific respondents (Greater China was just 19%).

Some organizations are using tech to add entirely new revenue streams—for instance, by diversifying from B2C to B2B using analytics offerings. Walmart’s Luminate analyzes consumer data to offer suppliers greater insight into competitive positioning. PepsiCo’s Digital Lab platform provides food service businesses with various digital tools and resources to help the companies improve their operations and customer experiences.

As promising as generative AI is, it’s just one part of the broader data portfolio (Exhibit 1). Much of the potential value to a business comes from traditional AI, business Yakov Livshits intelligence, and machine learning (ML). If CDOs find themselves spending 90 percent of their time on initiatives related to generative AI, that’s a red flag.