Salesforce on Measuring Agentic Work Outcomes

“Enterprises cannot vibe operate,” declares Madhav Thattai, GM and EVP of Salesforce AI, on this episode of Bloomberg Intelligence’s Tech Disruptors podcast. Thattai and BI senior technology analyst Anurag Rana discuss why Salesforce thinks the “SaaSpocalypse” narrative misses how agents change outcomes and how the company is trying to measure that shift with Agentic Work Units (AWUs) — a way to track work performed rather than just token inputs. Thattai outlines Salesforce’s four-part agentic enterprise framework: system of context, system of work, system of agency and system of engagement. The conversation explores how large-language model flexibility plus deterministic workflows are used to reduce “prompt doom loops,” improve latency and manage cost. The discussion also covers how Salesforce is monetizing agents via license bundles and consumption, and why AWUs and session-trace tooling are positioned as budgeting and operational aids for CIOs and CFOs.

AI adoption is moving from experimentation to execution, exposing gaps in data quality and governance. Qlik CEO Mike Capone joins Bloomberg Intelligence Senior Software Analyst Sunil Rajgopal to discuss why enterprises must build strong data foundations rather than rely on plug-and-play LLMs. “SaaS isn’t going away — it just has to be rewired,” Capone says, highlighting how AI is reshaping software architectures and limiting returns without strong data infrastructure. The discussion also covers Qlik’s positioning, competitive dynamics and how AI-driven productivity is influencing growth and product strategy.

The assumption that output grows linearly with headcount no longer holds. As AI tools drive a step-change in productivity, companies are rethinking their operating models. In this episode of the Tech Disruptors podcast, Owen Jennings, executive officer and business lead at Block, joins Bloomberg Intelligence Fintech and Payments Analyst Diksha Gera to discuss Block’s decision to reduce its workforce and how AI is reshaping both internal operations and the company’s products – from Cash App’s MoneyBot, which helps automate financial planning and budgeting, to Square’s upcoming ManagerBot, an AI-assistant designed to streamline SMB operations. Listen to hear more about how Block is deploying AI across its ecosystem — and how its approach differs from that of banks.

In banking, the AI question isn’t “Can you build it?” — it’s “Can you explain it, monitor it, and shut it off when required?” As the hype cycle moves past chatbots, a real competitive divide is emerging: institutions that can operationalize AI with auditability and control versus those layering copilots onto legacy workflows and hoping for the best. In this episode of Bloomberg Intelligence’s Tech Disruptors podcast, Capital One’s Chief Scientist and Head of Enterprise AI Prem Natarajan joins BI fintech and payments analyst Diksha Gera to discuss why the bank is building — not just buying — its AI stack, and what gives Capital One a technology edge over competitors. Listen in to hear more about the bank’s expansive approach to AI as a capacity multiplier rather than a means to cut costs.

Lumentum CEO Michael Hurlston and VP of Investor Relations Kathy Ta join Bloomberg Intelligence’s Jake Silverman on this episode of the Tech Disruptors podcast to discuss how optics are playing an increasingly critical role in networking inside and across AI data centers. They explore how the company is becoming a key supplier of systems and lasers to hyperscalers. Hurlston unpacks his broad and lengthy tenure as an executive across semiconductors and hardware and how it’s helping him tackle new challenges as the data center evolves. The conversation also covers how Lumentum’s past as a sleepier supplier to telecom networks positions it well to address today’s AI networking needs.

Reddit’s Chief Operating Officer Jen Wong discusses the impact of gen AI models on its platform and how the company is positioning itself in the era of chatbots and LLMs. Wong sits down with Bloomberg Intelligence’s Global Head of Technology Research Mandeep Singh to discuss  the company’s ads business and how it plans to leverage LLM search to boost engagement. All the metrics referenced in the episode are as of December 2025.

Resale is evolving from a fragmented, thrift-driven experience into a technology-enabled infrastructure layer for the apparel industry. James Reinhart, co-founder and CEO of ThredUp, joins Bloomberg Intelligence senior equity retail analyst Poonam Goyal on this episode of the Tech Disruptors podcast. They discuss how automation, machine learning and AI are reshaping the economics of secondhand retail. He explains the “single-SKU” challenge that makes resale fundamentally different from traditional e-commerce, and how ThredUp’s investment in supply-chain automation and data science aims to unlock scale, margin expansion and improved inventory velocity. Reinhart also explores the company’s shift toward AI-driven discovery, its expansion into direct-selling capabilities and the growing role of resale as a recommerce partner to brands. He outlines why he believes technology — not just consumer demand — will determine which resale platforms achieve durable profitability in the next phase of retail disruption.

“No great company became a great company because they saved a lot of money,” says Eric Boyd, president of Microsoft’s AI platform. “They became a great company because they delivered amazing innovative experiences.” In this episode of Tech Disruptors, Boyd explains to Bloomberg Intelligence Senior Technology Analyst Anurag Rana how Azure OpenAI Service, Azure Machine Learning and Azure AI Foundry fit together. He also discusses what’s required to move to broad usage from a pilot: securing enterprise data, retrieving the right context (including “IQ” tooling), evaluating prompts across models and managing costs with techniques like model routing.

“Not everything is an AI problem,” says IBM Software SVP and Chief Commercial Officer Rob Thomas. In this episode of the Tech Disruptors podcast, Thomas and Bloomberg Intelligence senior technology analyst Anurag Rana discuss IBM’s hybrid cloud and AI strategy, from Red Hat/OpenShift and containers for multicloud portability to why the mainframe remains the platform for real-time, high-availability transactions. Thomas outlines IBM’s “new enterprise stack” and a layered, multimodel approach where orchestration and proprietary enterprise data matter more than any single frontier model — especially as sovereignty requirements rise. They also explore how system-of-record companies are best positioned to succeed in the AI era.

AI demand is scaling and infrastructure complexity is rising. Vultr CEO JJ Kardwell returns to the Bloomberg Intelligence Tech Disruptors podcast with an update on the market’s AI cloud demand. He spoke to BI tech analyst Woo Jin Ho about production AI workloads, GPU utilization and lifecycle economics, global data-center strategy, supply-chain constraints and capital discipline, as well as outlining how privately held Vultr is positioning for durable growth in the industry’s next phase.