Tech Disruptors

AI’s expansion into enterprise use is exposing a gap between rapid prototyping and reliable deployment across the organization. Domino Data Lab CEO Nick Elprin joins Bloomberg Intelligence senior software analyst Sunil Rajgopal to discuss how model-driven organizations are putting AI to work in core-business settings, where governance and standardization are essential. As coding assistants enable domain experts to build full-stack analytics applications, “basic SaaS applications are pretty seriously threatened right now,” Elprin says. The conversation also explores why human-in-the-loop systems are still essential and how companies manage fragmentation risks as agentic AI evolves.

“We charged for outcomes with Fin…we’re charging when we did the work properly, and we weren’t charging when we didn’t,” Des Traynor, Intercom’s co-founder and chief strategy officer, tells Anurag Rana, senior technology analyst at Bloomberg Intelligence. In this Tech Disruptors episode, Traynor explains why Intercom chose to cannibalize its seat-based support software as a service to launch an AI agent that targets 60–70% resolution, and why outcome pricing changes everything from product design to unit economics. They also dig into what separates resolution from “deflection,” why most companies shouldn’t self-build support agents, how Intercom mixes models — including its own CX models — to optimize quality/cost and why 2026 is about expanding Fin from support into broader customer-facing roles.

Ericsson’s recent headway in securing contracts for 5G enterprise applications signals a rise in commercial deployments as business customers gain confidence in the technology’s potential to improve returns. In this episode of Bloomberg Intelligence’s Tech Disruptors podcast, Ericsson SVP and Head of Business Area Enterprise Wireless Solutions Asa Tamsons joins BI senior telecom analyst John Butler to discuss the outlook for enterprise 5G applications and how customers are using the technology to boost efficiency and generate higher returns. The discussion also touches on 6G and its potential to embed intelligence across business operations, partly through AI, while building on 5G’s ability to interconnect devices.

Mastercard’s push into stablecoin infrastructure, including its proposed acquisition of BVNK, alongside advances in enabling agentic payments, reflects an evolution rather than a disruption of its core business. In this episode of Bloomberg Intelligence’s Tech Disruptors podcast, Jorn Lambert, Mastercard’s chief product officer, joins BI fintech and payments analyst Diksha Gera to discuss how Mastercard is extending its value proposition around trust into new environments — from owning the “plumbing” of stablecoins through interoperability and multi-rail enablement to acting as the “intent verifier” in emerging agentic payments. Listen to hear more about how Mastercard is shifting from a card network to an intelligent “switch” of multi-rail platforms, as AI agents begin to navigate merchant catalogs and execute autonomous transactions.

Concentrix CEO Chris Caldwell joins Bloomberg Intelligence analyst Tamlin Bason to examine how AI is reshaping customer experience. As companies move from pilots to scaled deployment, Caldwell discusses how AI is enabling more personalized, real-time interactions, while introducing risks around consistency, trust and brand control. The conversation also explores the role of incumbents like Concentrix in bringing the scale needed to implement AI effectively, bridging the gap between emerging technology and enterprise execution. Caldwell shares where he sees value forming across the customer-experience ecosystem, and why protecting brand identity remains critical as automation deepens.

“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.

“If anyone’s going to disrupt Khan Academy, it should be us,” founder and CEO Sal Khan tells Bloomberg Intelligence Senior Tech Analyst Anurag Rana, discussing how AI can deliver personalized learning at scale if embedded in classrooms with teacher oversight, guardrails for minors and rigorous model evaluation. Khan explains Khanmigo’s early GPT-4 roots, why Khan Academy is going multi-model to match use cases like Writing Coach and how district packaging helps cover compute costs while enabling monitoring and accountability. He also lays out a vision of the 2030 classroom where AI reduces teacher planning and grading burdens, supports small-group instruction and enables richer assessment, while warning workforce disruption may arrive faster than society is prepared for.

Lightmatter CEO Nick Harris joins Bloomberg Intelligence’s Kunjan Sobhani and Jake Silverman to explain why lasers — not just chips — are the missing piece to making co-packaged optics practical at hyperscale. Harris unpacks Guide, Lightmatter’s VLSP light engine, and Passage, the company’s photonic interconnect platform, walking through real-world reliability, density and power trade-offs, and how new EDA and foundry partnerships (Synopsys, Cadence, GUC) move photonics into standard semiconductor workflows. The conversation covers near-package vs co-package optics, deployment timing, who the early buyers will be, and the milestones to watch as photonics shifts from lab demos to production racks.

Russia invasion of Ukraine “has completely reframed perceptions of drone utility and value. Where once high-end, exquisite systems dominated the procurement logic, today there’s a much clearer recognition that quantity and replaceability are just as critical,” says AV Chief Growth Officer Church Hutton. On this episode of the Tech Disruptors podcast, Hutton tells Bloomberg Intelligence senior defense weapons analyst Wayne Sanders how the landscape of drone technologies and the scalability of platforms must balance between rapid production and programs of record, while maintaining a technological advantage over adversary weapon systems. Critical to this process is reducing “cost per effect” so that we’re no longer shooting down $10,000 drones with million-dollar interceptors. AV and other defense tech companies continue to have this as their mission statement.

Ciena is expanding from its telecom optical roots to become a critical enabler of AI-driven data-center infrastructure. In this episode of Bloomberg Intelligence’s Tech Disruptors podcast, Ciena Executive Advisor Scott McFeely joins BI analyst Woo Jin Ho to discuss how the company’s optical technology has evolved alongside hyperscale cloud and AI workloads, from coherent optics and WaveLogic DSPs to optical pluggables for scale across applications. They also explore how AI is reshaping optical demand around and inside the data center, Ciena’s move deeper into the rack through its Nubis acquisition and how its expansion into AI changes its intermediate-term growth trajectory.

‘We’ve seen an incredible acceleration of true automation, where AI agents were able to fulfill a significant amount of engagement with a consumer, whether it be voice or chat-based,” says Scott Russell, CEO of NiCE. He sits down with Bloomberg Intelligence analyst Mandeep Singh to talk about the deployment of AI agents for contact centers. From fine-tuning of large language models to handling a high volume of transactions, the discussion focuses on the various considerations for AI agents related to customer service across a range of industries.