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6G and AI: This Time Is Not Different
/by Chris Antlitz, Principal AnalystThe telecom industry has become too focused on incrementally improving the traditional model of building, owning and operating networks rather than fundamentally questioning whether that model remains fit for purpose. Much of what is characterized as innovation today amounts to finding ways to squeeze more value out of existing assets, architectures and business models. These improvements are necessary, but they are unlikely to address the industry’s more fundamental challenge of revenue shrinking on an inflation-adjusted basis.
Lenovo’s Hybrid AI Push Puts Industry Solutions and Services at the Center of Its Growth Ambitions
/by Ben Carbonneau, Senior AnalystLenovo believes enterprises will run AI across devices, on-premises infrastructure and public clouds — a hybrid AI architecture — choosing where to process information based on data security, latency and operating costs. This core belief drives Lenovo’s investment strategy of building software, solutions and services around its wide-ranging hardware portfolio, spanning smartphones, PCs, workstations, servers and storage to support customers’ choices about where AI runs. For example, Lenovo is positioning itself for broader enterprise AI adoption by leaning into its Hybrid AI Advantage framework, which combines the company’s hardware, software and services to support the deployment of solutions from its AI Library.
Mavenir Bets the Mobile Core Can Become Telecom’s AI Control Point
/by Stephanie Long, Senior AnalystOperators are looking for ways their core can deliver value beyond connectivity, particularly as pressure mounts to reduce operating expenses and differentiate services. Mavenir is responding with a distributed-intelligence architecture that places AI and analytics inside network functions, at the edge or centrally, depending on use-case requirements. Its proposed progression from rule-based automation to predictive analytics and generative, agentic reasoning is designed to improve service quality, optimize power consumption, identify fraud and ultimately support more autonomous network operations.
Sapiens’ AI Transformation: Inside its Bet on Autonomous Insurance
/by Patrick Heffernan, Practice Manager and Principal AnalystFor the last nine months, Sapiens has been testing the possibilities of radical AI-enabled change, while continuing to support customers in a highly regulated and hidebound industry. New leadership has challenged the company to move at AI speed while establishing a new standard for quality. Sapiens has made a massive bet that the trust it has built with long-standing clients will carry over as the company shifts its commercial, delivery and technology partner models to a fully AI-enabled way of working. It is a bold bet; now comes the execution.
Infosys Moves From AI Experimentation to Enterprise Orchestration as Infosys Topaz Takes Center Stage in the Company’s Next Chapter
/by Bozhidar Hristov, Principal AnalystInfosys hosted more than 200 clients, partners, analysts and advisers during its flagship event, Infosys Americas Confluence 2026. The packed agenda included Partner Day and Analyst Day tracks, client stories, partner presentations and Living Labs demos of both Infosys- and partner-developed solutions and services. AI dominated the agenda, but the conversations were notably different than those at Confluence 2025. Last year, Infosys and its clients largely focused on the prerequisites for enterprise AI adoption, including data readiness, governance, architecture and talent. This year the discussion shifted toward what happens when enterprises actually begin scaling AI; the need to address rising complexity, agent governance, token economics, cybersecurity and model choice; and the ever-difficult task of proving business value. Infosys used the event to reinforce its ambition to become a leading enterprise AI services provider, positioning Infosys Topaz — and increasingly Infosys Topaz Fabric — as the enabling layer connecting models, applications, data business processes and partner technologies.
HCLTech Advances its Total Experience Services Through AI-led Operating Model Transformation
/by Kelly Lesiczka, Senior AnalystIn an ever-connected world, HCLTech established its Total Experience offerings to create a unified user and customer experience for its clients, removing pain points and friction across teams and departments. The transformation begins with the operating model, as many companies have different platforms and experience solutions across functions. The goal of the company’s experience solutions is to connect users across operations by optimizing and redesigning operating models.
Gemini for Industries: Context, Governance and the Changing Role of SI Partners
/by Catie Merrill, Senior AnalystThroughout 2026, Google’s Gemini for business has evolved from a set of components to a unified solution for practical AI. Today, it is used by 90% of the Fortune 100 and has become the fastest-growing product in Google Cloud history. Two complementary pieces exist: the application — which is designed to be the “front door” for the workplace, drawing on context from Workspace as well as other productivity apps (e.g., M365, Slack) — and the platform for building, customizing and operating AI. New FinOps capabilities and the inclusion of the Antigravity harness in all subscriptions are recent examples of how Google Cloud is addressing both sides of the portfolio, unlocking a strategic flywheel where Gemini creates demand and fuels usage of the Gemini platform. If Google Cloud can effectively deliver both as part of a unified solution, helping customers combat agent sprawl while staying true to its roots of openness and flexibility, it will take a big step to address one of AI’s central challenges: how to translate capable AI models into something that can scale at enterprise levels.
Trust at Speed: EY’s Mobility Practice Is a Catalyst for AI-era Workforce Transformation
/by Patrick Heffernan, Practice Manager and Principal AnalystTechnology and macroeconomic trends favor EY’s Mobility practice. Perhaps just as significantly, so do trends across professional services, including AI adoption, business model disruption, commercial model shifts, and an all-around recognition that the largest consultancies need to change to meet clients’ changing demands and AI-enabled expectations. For the last three years, TBR has heard from both EY leaders and EY clients that the firm’s Mobility practice is already a catalyst for that change.
Nokia Aims to Use Current Tech Transition to Strengthen Fixed Networks, Enter New Markets and Add AI Capabilities to its Core Technology
/by Stephanie Long, Senior AnalystThe fixed networks market is at an inflection point, with three major technology transitions underway across access, Wi-Fi and network management. TR-069* (technical report 069) is evolving to TR-369 (technical report 369), the first major hardware refresh toward Wi-Fi 7 is underway, and the migration from GPON to XGS-PON, and selectively to 25G and 50G PON, is progressing as these technologies advance. These shifts create a favorable window for Nokia to capture demand because hardware replacement is a logical time to pull through software modernization. Operators are simultaneously reconsidering how they manage the home, automate access networks and prepare fiber infrastructure for changing traffic patterns caused by AI adoption. Nokia is approaching this wave of progress with clearly defined road maps across relevant portfolio areas (e.g., Altiplano, Corteca, Quillion, PON) and is leveraging its hardware roots as the foundation for its AI story.
Setting the Pace: What Accenture, Deloitte and Infosys Signal for Professional Services in 2027
/by Patrick Heffernan, Practice Manager and Principal AnalystAI promises productivity improvements by off-loading repeatable, mundane tasks to algorithms and robots. If an IT services company or consultancy can do things faster with AI and automation, clients can reasonably expect their time-and-materials bill will decline. Accenture, Deloitte, Infosys and all their peers now find themselves — or, really, have found themselves since at least mid-2023 — challenged with managing the cannibalization that their AI investments may be bringing to their traditional IT services.