Microsoft have unveiled "Leading the Shift," a new Azure podcast exploring how enterprise leaders across sports, entertainment, healthcare, consulting, and financial services navigate the AI platform transformation. Senior Director Susan Etlinger highlighted insights from guests ranging from developers to data scientists, through to C-level executives discussing generative AI's impact on value creation and technology leadership.
The podcast's first eight episodes reveal five key themes from organisations implementing data, AI, and cloud technologies in previously unthinkable ways. Leaders understand generative AI's opportunity extends beyond content generation to discovering, translating, and understanding relationships among vast data types including customer service touchpoints, financial reports, and drug candidates.
Shirli Zelcer, Chief Data and Technology Officer at Dentsu, emphasised generative AI's ability to connect entire customer journeys, stating customer reviews and calls become "very meaningful signals and even more so when a brand knows where in the journey that consumer sits." Hiren Shukla, Global Neurodiversity and Inclusive Value Leader at Ernst & Young, described multimodal capabilities enabling "compressed innovation" by recognising employee potential that would otherwise go unrecognised.
Experimentation emerges as crucial for building expertise with probabilistic generative AI technologies. Perry Hewitt, Chief Marketing and Product Officer at data.org, advocates being "bold, to experiment, to find ways to incorporate data and AI into your line of business or to your work in small, incremental, low-risk ways." Ade Famoti, Global Head of Research Incubations at Microsoft Research Accelerator, characterises the current period as "an AI renaissance" requiring rapid iteration culture.
Leaders maintain clear North Star approaches while experimenting. Charlie Rohlf, Vice President of Stats Technology Product Development at NBA, emphasises explaining project rationale to engineering and data science teams for better outcomes. Cristina Pieretti, GM of Digital Insights at Moody's, describes leadership focus on understanding disruption implications for company operations, efficiency, and customer impact.
Trust building from project inception through customer co-creation proves central to adoption success. Organisations recommend involving legal and governance teams early while establishing strong data governance, content safety, model evaluation, and bias mitigation processes. Teresa Tung, Global Lead of Data Capability at Accenture, advocates treating proprietary data as strategic assets, noting models deliver identical results to competitors without differentiated data inputs.
The platform shift requires organisations to rethink data as products rather than byproducts, with generative AI enabling combination of unstructured data with first-party and third-party sources for enhanced insight and predictive capability. The probabilistic nature of generative AI contrasts with deterministic technologies, demanding experimentation-based capacity building over traditional waterfall methodologies. Leaders position current developments as early-stage opportunities, with significant untapped potential in existing data capabilities.