Tech Disruptors

With the latest energy shock pushing UK inflation higher while economic growth remains subdued, investors are questioning whether markets have priced too much Bank of England tightening. Jack Meaning, UK chief economist at Barclays, joins Bloomberg Intelligence chief US interest rate strategist Ira Jersey to discuss that and more on this Macro Matters edition of the FICC Focus podcast. Meaning explains why Barclays expects inflation to climb above 3% in the second half of 2026 but sees little evidence of the wage or second-round effects that would make the increase durable. The two discuss why keeping Bank Rate at 3.75% already represents a meaningful tightening relative to earlier market expectations and how restrictive financing conditions and labor-market slack are weighing on growth. They also explore whether improving investment intentions — including spending tied to artificial intelligence — can provide support. The conversation examines Brexit’s lingering impact, the UK’s difficult fiscal choices and why Barclays expects the Bank of England to remain on hold this year before inflation moves back toward target in 2027. The episode concludes with a look at the central bank’s upcoming quantitative-tightening decision and the debate over continuing active gilt sales.

“Hopefully in three or four years, we will be on 50% of all the devices on the planet,” Ramin Hasani, co-founder and CEO of Liquid AI and a machine-learning scientist at MIT’s Computer Science and Artificial Intelligence Laboratory, tells Bloomberg Intelligence senior technology analyst Anurag Rana. In this episode of the Tech Disruptors podcast, the pair discuss how Liquid AI’s alternative to transformer architecture could make foundation models dramatically more efficient, allowing specialized intelligence to run directly on cars, phones, laptops and other edge devices rather than relying on data centers. Hasani explains how Liquid AI is working with companies including Mercedes-Benz and Shopify while developing personalized and proactive agents that could turn its models into an intelligence layer spanning devices, enterprises and the physical world.

“The hardest challenge in enterprise agent deployment is not generating them; it’s the accountability,” Kristin Milchanowski, chief AI and quantum officer at BMO Financial Group, tells Bloomberg Intelligence senior analysts Paul Gulberg and Anurag Rana. In this episode, the group discusses BMO’s AI profit target of $1 billion by 2030, how the bank is embedding AI into core workflows and why agentic systems still require strong human oversight, governance and measurable benchmarks. Milchanowski explains how BMO is designing for model change with a hybrid infrastructure, exploring small language models for focused workflows, and prioritizing measurable business value over token consumption as it expands AI across the enterprise.

Reducing inefficiencies across financial services, automating workflows and maximizing available cash flow for small- and medium-sized businesses (SMBs) is central to BILL’s mission. On this episode of Tech Disruptors, the company’s chief product officer, Mike Cieri, joins Bloomberg Intelligence analyst Niraj Patel to discuss the creation of a future financial platform that covers payments, spending and expenses, accounts payable, financial planning and analysis and more. He explains how BILL is leveraging AI across its portfolio, which serves close to 500,000 SMBs, and talks about the fragmented payments landscape, customer priorities and the company’s transaction agents.

“The bottleneck isn’t really having ideas; the bottleneck is execution,” Gautier Cloix, CEO of H Company, tells Bloomberg Intelligence Senior Technology Analyst Anurag Rana. “What we do is basically [make] execution infinite so we can focus on intention and ideas and strategy.” In this episode of Tech Disruptors, the pair discuss how computer-use agents can operate enterprise software through existing user interfaces, enabling companies to automate workflows without first rebuilding, migrating or integrating their technology stacks. Cloix also explains why H Company combines specialized, lower-cost models with forward-deployed engineers to target measurable ROI, turning legacy software into an asset and creating an execution layer across disconnected enterprise systems.