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Comcast 3Q26 Earnings: Convergence and Cost Transformation Seek to Ease Broadband Pressures as Business Services Growth Slows

Harsheeta Arora — Mon, 02 Nov 2026 05:00:00 GMT

Comcast announced its 3Q26 financial results on October 22, 2026, reporting revenue of $29.3B, down 6.1% year over year (YoY) from $31.2B. On a pro forma basis, which adjusts for the separation of Versant (completed on January 2, 2026) and the sale of Sky operations in Germany (completed on May 31, 2026), revenue increased 0.5%. Connectivity & Platforms revenue declined 2.7% to $19.7B, while Content & Experiences revenue increased 6.5% to $10.5B.

Adjusted EBITDA was $9.1B, down 5.8% YoY and up 0.8% on a pro forma basis. Connectivity & Platforms adjusted EBITDA declined 4.4% to $7.6B, with a margin of 38.6% compared with 39.3%.

Domestic wireless line net additions were 368K compared with 414K in 3Q25, bringing total domestic wireless lines to 10.6M, up 1.6M over the last 12 months. Domestic broadband residential customer net losses were 144K, compared with 91K a year earlier, and domestic video customer net losses were 274K compared with 257K. Management reported that approximately 45% of broadband customers are on 1Gig and above speed tiers. Premium Unlimited plans represented approximately 40% of postpaid phone connects, while approximately 70% of free lines converted to paid relationships.

Residential Connectivity & Platforms revenue declined 3.5% to $17.0B, and adjusted EBITDA decreased 5.8% to $6.1B, which management said reflects investment in its go-to-market strategy. Domestic broadband revenue decreased 4.7% because of lower average rates and fewer customers, while domestic wireless service revenue increased 14.7% and video revenue decreased 8.7%. Management said domestic broadband average revenue per user (ARPU) declined 2.9%, and domestic convergence average revenue per account (ARPA) declined 0.5%, with YoY declines in both metrics narrowing sequentially. Business Services Connectivity revenue increased 2.7% to $2.6B, led by enterprise solutions, and adjusted EBITDA increased 1.7% to $1.5B, with a margin of 55.9% compared with 56.4%.

Free cash flow decreased 14.8% to $4.2B from $4.9B.

AI Sourcing Controls and Pricing Terms Decide Who Keeps Leverage — Three Sourcing Considerations for Tech Leaders: What You Buy, How You Manage Providers, and What You Commit to

Tiffany McCormick — Fri, 30 Oct 2026 04:00:00 GMT

This IDC Tech Leader Presentation describes three sourcing considerations for tech leaders: what you buy, how you manage providers, and what you commit to. AI sourcing is no longer a onetime contract, and buyers keep leverage by pairing the controls that protect the bill with the pricing terms that protect the rate. Drawing on IDC's August 2026 AI Economics and Cost of Ownership Survey (n = 1,184) and its Effective Agent Cost Management framework, this document describes three sourcing considerations for technology leaders. First, buyers should know what they are buying. Most AI arrives inside software they already own, and buyers choose providers on security and quality before exit terms. Second, buyers should manage providers as a portfolio. Third, buyers should know what they are committing to. Mature buyers commit for longer, and most expect cost per task to rise, so a longer commitment is a bet on the rate. The terms that lock the rate, the model, and the renewal therefore matter more than the discount. Sourcing leverage is built at selection, kept in operation, and spent at renewal.

"AI sourcing is no longer a contract signed once. Buyers keep leverage when they pair the controls that protect the bill with the pricing terms that protect the rate and when they clarify what kind of predictability a vendor is offering," says Tiffany McCormick, senior research director, AI Monetization, Pricing Strategies, and Business Models.

Effective AI Agent Cost Management: What Executives Must Understand to Transform Unpredictable AI Spend into Strategic, Auditable Investments, and How to Enable Your Teams to Get There

Fri, 30 Oct 2026 04:00:00 GMT

This IDC Tech Leader Presentation is based on IDC's AI Economics and Cost of Ownership Survey, August 2026 (n = 1,184). To help executives turn unpredictable spend into auditable, strategic investment, the document sets out a four-phase framework covering plan and budget, source, implement, and operate. Agentic AI is scaling faster than most organizations can govern or budget for, and its costs behave differently from the cloud spend finance teams already know how to manage. Agent costs rise with conversation length, tool-call depth, and task complexity, not with anything provisioned in advance.

"When it comes to AI economics, most companies are focused on the wrong things. They're too busy counting tokens. That's important, but IDC research shows there are at least 10 other critical factors in planning for AI costs that companies aren't considering, and most don't have the mechanisms in place to track them effectively. Organizations that build visibility into these factors now will be far better positioned to scale AI profitably," says Shari Lava, group vice president, Artificial Intelligence, Data, and Automation at IDC.

Google Introduces Gemini 4 Argon, a New Multimodal Reasoning Model at the Frontier of Artificial Intelligence for Complex Enterprise Knowledge Work

Tim Law — Fri, 30 Oct 2026 04:00:00 GMT

Google announced the global availability of its new Gemini 4 Argon model. The new release adds to the fierce competition and continuous innovation in new model capabilities. It reasserts Google’s intent to compete for enterprise workflows and widens the aperture on the nature of what is considered knowledge work.

"The Gemini 4 Argon release continues the rapid pace of new frontier model introductions," said Tim Law, Research Director, AI and Automation at IDC. "The new release heightens the competition for diverse AI and agentic automation use cases for both traditional functional workflows and complex, long-running, technical and specialized use cases."

IDC MarketScape: Worldwide Public Cloud AI Infrastructure as a Service 2026–2027 Vendor Assessment

Dave McCarthy, Jasdeep Singh, Taranvir Singh — Fri, 30 Oct 2026 04:00:00 GMT

This IDC study evaluates a select set of providers of public cloud AI infrastructure as a service, scoring accelerated compute, high-performance interconnect, AI-optimized storage, and the orchestration and consumption layer across both training and inference workloads.

The assessment finds that accelerator supply is no longer the dominant variable. Headline cluster figures have converged, and competitive separation now comes from the layers surrounding the accelerator: storage metadata performance, fabric behavior, automated fault recovery, and the commercial constructs through which constrained capacity is secured. Fabric choice, open standards participation, consumption model design, and facility engineering have all become points of differentiation, while inference is separating from training as a distinct infrastructure discipline.

"AI infrastructure has become a strategic decision rather than a procurement exercise," said Dave McCarthy, group vice president, Cloud and Datacenters, Enterprise Infrastructure, at IDC. "As organizations move AI from experimentation into production, the platform beneath the model increasingly determines what it costs to train, how quickly it reaches users, and whether it can be operated at scale under real governance constraints."

India Case Study: Building Nugget — How Zomato Scaled Its Conversational AI Platform to Production on Amazon Web Services

Rajiv Ranjan — Fri, 30 Oct 2026 04:00:00 GMT

This IDC Perspective documents the stages of Zomato's modernization to develop Nugget, a robust, modern conversational AI–enabled CX platform. The case study discusses Nugget's development, its usage internally by Zomato employees, and its launch to the external market and adoption. It also highlights what value Amazon Web Services (AWS) provided in building and launching Nugget and why enterprises should consider Nugget.

"Conversational AI platforms can help organizations modernize fragmented, legacy CX processes into a unified, multichannel, and multilingual experience that delivers personalized interactions and scales on demand to support a growing customer base," says Rajiv Ranjan, associate research director, IDC.

Managing Risk when Financing IT Assets Given AI Demand's Reshaping of Hardware Markets

Lara Greden — Fri, 30 Oct 2026 04:00:00 GMT

This IDC Perspective helps technology leaders and procurement professionals negotiate IT asset financing in a market where AI demand is making residual values and refresh timing less predictable, with guidance on pricing each asset class separately and maximizing flexibility in lease terms.

"With AI reshaping hardware supply and pricing, fair market value of used assets now varies distinctly by asset class," said Lara Greden, senior research director, Infrastructure Services, IDC. "Technology leaders who price each asset class on its own and use leasing contracts to build in flexibility will be better positioned to manage cost and risk as market conditions change."

OpenText World 2026: Seeking to Achieve Governed, Production-Ready Software with AI-Generated Code

Jim Mercer, Melinda-Carol Ballou — Fri, 30 Oct 2026 04:00:00 GMT

At OpenText World 2026 in Orlando, OpenText positioned itself as a trusted data and context layer beneath enterprise agentic AI. For software delivery, the most consequential news came from its application delivery management (ADM) business, which showed how Aviator agents, a traceable knowledge hub, Model Context Protocol (MCP)–based interoperability, bring-your-own-LLM deployment, and governed self-healing tests aim to close the gap between how fast AI generates code and how well organizations can prove it is ready for production.

Payment Data and Its Value to Merchants

Aaron Press — Fri, 30 Oct 2026 04:00:00 GMT

This IDC Perspective argues that payment data is a strategic asset for merchants, offering far more value than its traditional use in reconciliation and reporting. The most forward-thinking merchants work with their payment partners to leverage payment data to inform business operations, optimize payments, and support AI-driven use cases. As agentic commerce matures and software agents begin to transact on behalf of customers, the need for clean, connected payment data will only intensify. Merchants that invest in data quality and integration will be best positioned to recognize, authenticate, and serve their current and future customers.

"Payment data isn't just a record of transactions. That data is the most reliable, untapped intelligence merchants have to outpace fraud, optimize AI, and drive smarter growth," says Aaron Press, research director, Worldwide Payment Strategies, IDC.

Tech Leader Survey Spotlight: Is AI Running Payer IT Operations Yet, or Is It Still a Pilot?

Inci Kaya — Fri, 30 Oct 2026 04:00:00 GMT

This Tech Leader Survey Spotlight presents data from IDC's January 2026 AI and Cloud-Native Software Delivery Survey. It provides directional guidance based on 31 healthcare payer respondents. While nearly half of respondents were based in the United States, the survey was fielded globally.

Health plans are displaying widespread AI activity, but with thin production levels. Software delivery initiatives that involve AI are approximately two-thirds in prototyping or R&D and one-third in production. This sentiment is repeated in engineering teams that work on the experimentation phase more than production phase, though IT service desk is emerging as a strong exception, with a growing number of examples in production.

The main barriers to shifting from pilots to production are ownership, skills, and regulation rather than ROI. Regulations and compliance is the most-cited significant or critical challenge, followed by unclear ownership of AI responsibilities (i.e., who owns each AI pilot project and how decisions are made to go forward or not) and the skills gap. Such barriers inevitably delay legacy modernization plans, leaving them in the experimentation phase.