This article was written by Leila Shaban, Research Associate at Metis Strategy
Thank you to everyone who attended and participated in the 17th Metis Strategy Digital Symposium. Highlights from the event are below. Check out Metis Strategy’s Youtube channel and Technovation podcast in the coming weeks for recordings of each conversation.
Companies continue to make progress in their AI journeys, deploying the technology to drive efficiency, productivity and innovation. Technology leaders are focused now on driving adoption, generating buy-in for new initiatives, and rolling out new training programs to ensure teams across the enterprise are able to take advantage of what AI has to offer. Below are a few highlights from the event:
Building a foundation for AI at scale
Nearly all CIOs on stage said scalable infrastructure and high-quality, accessible data are key to driving value from AI initiatives. Over the past few years, many organizations have focused on building data platforms, shifting to cloud and rethinking ways of working in order to deliver AI at scale. “Having a really good data infrastructure is foundational to taking advantage of any of these generative AI capabilities,” Priceline CTO Marty Brodbeck said. Many speakers noted their current efforts to get reliable data into the hands of more teams across their organizations.
Nearly half of MSDS attendees said that the rapid evolution of AI, among other macro issues, will have the biggest impact on their organizations in the year ahead
Exploring new use cases
Many organizations continue to train generative AI on internal knowledge bases to streamline processes and enable more self service. CIOs also see potential around developer productivity.
Bristol Myers Squibb receives thousands of calls from physicians and nurse practitioners each day requesting information about specific, often technical, topics, Chief Digital and Technology Officer Greg Meyers said. MDs on the other side of the call often find those answers in internal documents. Now, an AI chatbot trained on the company’s knowledge base can search through the documents to retrieve answers to these questions much faster. With enough fine tuning, Meyers noted the chatbot could constrain search results to trusted documents and help agents provide near-immediate answers to customer queries.
At UPS, Chief Digital and Technology Officer Bala Subramanian recently launched an internal AI tool for email which can process the tens of thousands of customer emails UPS receives on a daily basis, connect relevant information across internal policies and procedures, and generate responses for contact center employees. This ultimately improves worker productivity and reduces response time. UPS also launched an AI chatbot to help employees answer HR questions. Subramanian noted that the company is proceeding slowly due to the sensitive information and personal data in HR systems, and emphasized the critical role of risk management and governance.
At AstraZeneca, AI is significantly reducing the amount of time it takes to conduct research. Cindy Hoots, Chief Digital and Information Officer, described a generative AI-enabled research assistant that quickly searches both internal and external data to answer complex scientific questions. The assistant has helped reduce the time it takes to conduct a literature review from months to minutes, she said. Hoots is now focused on scaling AI adoption. About 15,000 employees use the research assistant, she said, while roughly 5,000 use Copilot solutions and almost 80,000 have access to AstraZeneca’s internal ChatGPT.
At KB Home, employees evaluate a number land deals across 35 markets every week. Aggregating property data from different sources to determine whether to make an acquisition used to take 30-90 days, CIO Greg Moore said. With AI, KB Home can now complete the process in less than two weeks. The faster turnaround now enables the company to make more evaluations and manage more potential deals in the pipeline.
Developer productivity is another area of rapid experimentation. Many of the tools offered by major vendors are in their early days and have room to grow, said Brodbeck of Priceline. The team is exploring solutions that can learn from Priceline’s codebase and provide a richer and more contextual experience. Whether for code generation or another use case, Brodbeck said companies will likely need to deploy retrieval-augmented generation (RAG) to deliver more productivity.
At Augment, CEO Scott Dietzen is thinking about how to retrieve knowledge from internal codebases in a way that protects intellectual property and reduces the risk of leaking sensitive information. The team started with basic engineering tasks that can make developers more productive rather than trying to replace them altogether. Demand for these kinds of tools will last for at least a decade as organizations produce more software, Dietzen said.
The top use cases for digital assistants/copilots that are driving the most value for MSDS attendees are code generation, self-service chatbots, and enterprise search/knowledge management
Bringing the organization along on the AI journey
To drive a common understanding and widespread adoption of AI, CIOs have increased their focus on storytelling and talent development.
At Wilson Sonsini, Chief Information Officer Michael Lucas is focused on cascading AI communications across the firm. His team started with a general awareness campaign. That included employee town halls to communicate the broader strategy as well as AI-centric briefings to partners. Given the sea of media coverage about AI, Lucas encouraged leaders to develop their own elevator pitch to help their organizations clearly understand the company’s AI strategy. Driving a common understanding across the firm is key to driving adoption. “We feel like we need to learn, understand, enrich, and then apply and operationalize,” Lucas said.
At Liberty Mutual, Global Chief Information Officer Monica Caldas is delivering customized employee training and connecting it to the company’s capacity demands across 27 countries. It’s part of a workforce strategy plan called “skills to fuel our future.” First, the company surveyed more than 5,000 employees to determine their skill level around topics like data, data engineering and software engineering. Next, the company mapped over 150 skills, connected them to 18 domains, and assessed how and where to invest in training.
Now, Caldas and her team are helping employees apply that training to a variety of career paths. Instead of a traditional career development ladder, Liberty Mutual is evaluating how to map skills to different jobs and create a “jungle gym” or “lattice of opportunities.” The focus on specific skills, Caldas said, “will help you position your capabilities as a tech organization not just for today, but also plan out where it’s going.”
Education at the executive level is also critical. To bring executives along on the journey, Caldas introduced a program called Executech that helps improve organizational data literacy and elevates the digital IQ of decision makers. Enhancing teams’ tech acumen gives leaders the confidence to start conversations early about important technology topics like API integration.
AI adoption may not be uniform, and there is still lots to learn about how it will impact specific roles. At Eli Lilly, employees who have incorporated AI tools into their workflow are reluctant to give them up, said Diogo Rau, Chief Information and Digital Officer. However, widespread adoption is a continuous and sometimes challenging process, “a lot harder than anyone would guess,” Rau said.
Rau often gets more questions about the risks of AI than how it can be used to improve products and services. Another challenge is that teams excited about creating AI bots aren’t always excited about maintaining or training them. “There are lots of good firefighters, but not every firefighter wants to be a fire inspector,” he said.
62% of technology executives who attended the Metis Strategy Digital Symposium anticipate that the most significant impact that AI will have on talent is increased productivity
Leveraging ecosystem partners
Achieving the transformative potential of generative AI will require collaborating with networks of vendors, startups, peers, and academics. In addition to providing technology solutions, these ecosystem partners can help upskill employees, explore emerging challenges, and prototype new use cases.
Amir Kazmi, Chief Information and Digital Officer at WestRock, draws learnings from both established technology partners and startups. He also brings in academics and peers from other companies to share wins and lessons learned about generative AI.
Regal Rexnord’s Tim Dickson, Chief Digital and Information Officer, uses hackathons and internal events with vendor partners to increase the company’s digital IQ. The company also offers self-paced training from about 10 partners that includes pathways to certification. In the past seven months, more than 100 employees have received training on GenAI fundamentals from Databricks and robotic process automation from UiPath, as well as certifications from Microsoft Copilot. Even if employees don’t use these tools every day, increasing the number of people with technical skills means more individuals “can at least help, or even lead, these initiatives across the organization,” Dickson said.
CommScope CIO Praveen Jonnala, like many other technology executives, is thinking about how to drive a cultural shift around AI. He spends about 80% of his time on organizational change management and culture. He is also leaning into existing partnerships to take advantage of new AI solutions and educate teams. For example, he took business teams to Microsoft for a full day to learn more about the technology and its ability to unlock new business opportunities.
