Thank you to everyone who attended and participated in the 14th Metis Strategy Digital Symposium. Highlights from the event are below. Stay tuned to the Metis Strategy Youtube channel and Technovation podcast in the coming weeks for recordings of individual panel discussions. We look forward to hosting the next Metis Strategy Digital Symposium in December – more details to come soon.
As generative AI continues to flood the headlines, technology and digital leaders are busy discerning hype from reality and exploring use cases that can deliver tangible value across their organizations.
While many companies have used AI in their operations for a while, the rapid rise of generative AI has drawn outsized attention from colleagues well outside the IT department. As a result, many CIOs and their peers have turned their focus toward the tools, processes, and skills needed to take advantage of the emerging technology at scale. Tech leaders are also honing their storytelling skills as they paint a picture for colleagues and customers of how AI-based technologies can drive growth and deliver new, value-added experiences.
In conversations with technology leaders across a variety of industries, we have found that those most successful in their AI endeavors so far are driving excellence across four overlapping workstreams: educate, explore, experiment, and expand. The speakers at this year’s Symposium were no exception. In order to prepare their organizations for an AI-driven future, they noted the following priorities:
Building cross-functional AI teams
Many organizations are taking an interdepartmental approach to developing AI strategies, bringing together stakeholders from across the business to prioritize use cases, build solutions and lead change management.
At Total Quality Logistics, CIO Ryan Kean built a Center of Excellence with 12 people across business units to evaluate new automation use cases, assessing whether or not to develop them based on expected value, tangible benchmarks, and reusability across the enterprise. Kean noted that while a decentralized approach may work for some organizations, it could lead to chaos in others if citizen development happens in silos. At TQL, the CoE model has helped to ensure proper governance, monitoring and development of new solutions.
Similarly, at real estate giant Cushman & Wakefield, Chief Digital and Information Officer Salumeh Companieh’s team has developed an AI task force that includes members from departments including cybersecurity, legal and procurement, to name a few. The task force has developed a standardized process that is helping CBRE actively review 200 use cases globally, delivering necessary governance while focusing on driving client value, market differentiation, and delivering unique insights.
Measuring customer and employee experiences
Speakers noted the critical role advanced AI tools can play in enhancing the digital experience for customers, but emphasized the need for a quality data foundation and clear measures to ensure progress is made.
Keeping customers and employees front and center will be key to enabling increased value and competitive differentiation with AI. To do that, technology leaders must continue to measure and assess progress on these initiatives regularly. DXC Technology CIO Kristie Grinnell conducts both employee NPS and external NPS surveys to measure whether her department is providing the tools and data that create frictionless experiences across the board, noting that both of those measurements should go up as the digitization journey continues. Grinnell also uses sentiment analysis to understand how employees are feeling and uses that feedback to guide employee experience initiatives. She noted that embracing accountability and ownership for specific services over the past years has helped push internal NPS scores from the low 20s to the mid 30s.
The most insightful methods that leaders use to gauge internal and external customer satisfaction and experience are Net Promoter Score (NPS/eNPS) and Customer Sentiment Analysis
At the Home Depot, CIO Fahim Siddiqui noted the virtuous cycle between great employee experience and customer experience: “If you take care of your associates, they will take care of your customers, and everything else takes care of itself.” To ensure that he is providing the right digital features and capabilities, Siddiqui provided all 400,000 customer-facing associates with a handheld device that connects them to the data and insights they need to help customers throughout the network. He also noted that this process sometimes involves interacting with a generative AI model that provides natural language responses to associate queries. Siddiqui noted that employee engagement has reached its highest level, and positive leadership behaviors are also on the rise.
Driving strategic automation
Generative AI tools have created new opportunities to automate and enhance a range of business processes. It is shifting the conversation around automation from one solely of efficiency to one of organizational effectiveness and growth.
One of the quickest ways that technology leaders have unlocked value for their customers and employees is training chatbots on company knowledge bases, ultimately reducing the time it takes to access critical information, answering queries in an easy to understand way, summarizing documents, and enhancing internal search and support. During peak tax season, Intuit employs 20,000 employees to provide advice to customers, resulting in 25 million conversations between customer agents and customers. To extract insights from these conversations and increase agent productivity, CIO Rajan Kumar has been employing AI/ML to provide automatic responses. Kumar’s team is now exploring and implementing a similar chatbot and user interface to provide support for internal employees around IT help desk, HR and procurement questions related to the employee experience.
The top generative AI use cases that MSDS attendees are prioritizing are answering customer queries, summarizing documents, and enhanced internal search/support
Driven by accelerated customer expectations, KeyBank developed a virtual assistant, called MyKey, to connect customers to the contact center and intelligently route support questions to staff faster and more intuitively. CIO Amy Brady has already seen value realized from these digitization efforts, including improved revenue, delivering more to clients with self-service, and improving the job of support agents while reducing turnover in support centers. She shared how improving the agent experience reduced uncertainty around automation. “We can be aspirational and get people engaged, driven by the impact,” she said.
Evolving their approaches to talent development
The rapid rise of generative AI has reignited conversations about how technology will change the way we work. It’s early days, but it’s becoming clearer that successful enterprise adoption will require not just new tools and processes, but also new skills and mindsets. Because generative AI doesn’t require users to know how to code, and doesn’t always require technical experts to drive these applications, the talent paradigm is changing. The shift is prompting technology leaders to reassess talent strategies and the skillsets required to prepare companies to be future ready.
Frustrated with many existing corporate education tools, Mars Global Vice President Shubham Mehrish and his team set about rewriting the playbook to create a more digitally savvy workforce. Mehrish is focused on education at every level of the organization, both top-down and bottom-up, and uses a range of educational and storytelling approaches to communicate with different stakeholders. The rise of AI is also prompting him to think differently about what he is looking for in technologists. Some of the key traits that he believes will mark successful candidates moving forward include curiosity, collaboration, and experimentation.
About one third of MSDS participants said that they are focused on general awareness and basic education in their AI talent development programs
Paramount CIO Lakshman Nathan reflected on the possibility that many companies won’t necessarily need data science or machine learning experts to drive AI applications, changing the way he approaches talent strategy. He is also working to increase general awareness of AI across the organization, including re-educating teams on technologies and processes that already exist inside the organization. “Business users are technologists now,” Nathan said. To increase general AI awareness, Nathan’s team set up a central site for everyone at the company to understand the AI process and get on the same page. The effort is collaborative across security, privacy, and technology teams to evaluate and expedite best use cases.
Aligning AI initiatives to business strategies
In order to generate the best value out of AI, technology leaders have to take a strategic approach aligned to business strategy. While there are many potential use cases for AI, technology departments are in a key position to assess the current and future state of AI-enhanced organizations tailored to specific business goals and industry requirements.
Assessing the best AI strategies to generate value requires thinking about the overall ecosystem and value chain. At NRG Energy, Chief Data and Technology Officer Dak Liyanearachchi is having the Data organization and the IT organization pull data together to focus more on the cost-benefit analysis: “will it generate the value we want?” At the same time, Liyanearachchi is evaluating the role that AI and generative AI will play in shaping the energy industry. He said that AI and technology enables his teams to focus more on the demand side of the energy grid and drives services to create better transparency around energy consumption for customers and households.
CIOs have to make sure they have the basics down before investing in new transformation. To prepare for tackling generative AI strategy and change management, Western Digital’s CIO Sesh Tirumala is looking at two buckets: perform and transform. He emphasized that leaders “get the keys to have a transformational agenda only if you are doing a good job in your perform.” After aligning on the fundamentals and the forecasting view, leaders can prepare their organization to be data-driven with action- and decision-making moving forward. “We don’t just manage for today and yesterday, but align on where we need to be [in terms of] talent strategy, outsourcing strategy, and IP […] to think about the problems of the future. How do you prepare and inspire the organization to look 3-5 years out?”
The majority of respondents at the Metis Strategy Digital Symposium indicated that they are either developing/defining AI strategy or implementing AI strategy across some teams
