Enterprise big data and analytics cuts through the hype to make sense of data collection, storage, management, dissemination, and discovery technologies, all employed collectively as a means of realizing corporate efficiencies and uncovering business opportunities.
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• AI-driven conversational discovery experience boosts the relevancy of marketplaces among broader audiences.
• Network services evolve into consumable and programmable products via enterprise agents.
Agentic AI innovations have boosted hyperscaler marketplaces’ relevance, and global telecommunications giants are taking notice.
Continue reading “Agentic AI Transforms the Marketplace UX as Infra Services Become Consumable Products”
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• Technology vendors are investing in forward deployed engineers to adapt AI solutions to meet customer needs.
• Systems integrators are working alongside their technology partners to help enterprises accelerate their AI adoption and ensure business outcomes are met.
It is widely reported that only a small percentage of firms that have conducted AI pilots are moving them into production. Even fewer enterprises have been able to scale their AI initiatives across multiple business functions. Based on GlobalData’s observations and discussions with enterprises, there has been greater success in AI implementations among large enterprises that have engaged a systems integrator or consulting firm to work alongside their technology partners, including hyperscale cloud providers and AI model companies (e.g., Anthropic and OpenAI).
Continue reading “Systems Integrators Adopting the FDE Model with a Focus on Business Outcomes”
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• While IP voice is less ubiquitous, when it matters it, it really matters
• Agent-to-agent communication adds a new paradigm to IP voice services
Calling IP voice a legacy service is a little unfair, but only a little. Innovation in this arena is still happening as can be seen by BT’s recent launch of its automated UC edge platform designed to help enterprises move numbers between UC platforms automatically. However, a recent and stark counterpoint to this is Lumen’s decision to exit the IP voice market.
Continue reading “Agentic AI May Give IP Voice a New Lease on Life as Legacy Decline Continues”
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• Meta will need to shed its consumer-centric image to gain traction in the business market, even if it only targets smaller organizations.
• Convincing organizations that they can trust Meta to secure personal information and corporate intellectual property will take time and effort.
On Monday September 28, 2026, Meta announced plans to enter what is already a crowded enterprise AI market. It will develop Meta Enterprise Platform, a collection of tools and services that will help business customers implement their own AI strategies. Few details were shared other than the platform will incorporate Muse agent, Meta Business Agent, Muse API, Muse Code, and other solutions.
Continue reading “Meta Will Need to Shed its Consumer-centric Image to Gain Ground in Enterprise AI”
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• Three voice-activated features coming to Google Workspace reflect a broader trend of AI becoming incorporated into everyday workflows.
• The features also mirror how vendors are opening their team collaboration platforms to support the multi-platform environment in which their users operate.
Google recently announced three voice-activated AI features coming soon to Google Workspace. ‘Gmail Live’ lets users ask conversational questions to retrieve information from their Gmail inbox such as “What’s my flight’s gate number?”. Users can talk to ‘Keep Live’ to capture ideas that cross their mind and turn them into organized, actionable notes. With ‘Docs Live’ users can engage in real-time conversation to create documents on the fly. Although Workspace users cannot avail themselves of the features quite yet, ‘Gmail Live’ and ‘Keep Live’ are available to Google AI subscribers on the Plus, Pro, and Ultra plans while ‘Docs Live’ is reserved for Pro and Ultra subscribers.
Continue reading “Google is Keeping Workspace on the Cutting Edge”
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Nokia didn’t use the term “Physical AI” in its announcement, but its new Cognitive Operations (CO) platform reads like a carefully constructed argument for why it belongs in that conversation. Physical AI is not just AI applied to industrial data; it is AI that perceives, decides, and supports action in the physical world, often in real time, often with incomplete connectivity, and often where failure carries operational, financial, or human consequences. This is the exact scope that Nokia is targeting with CO, initially for mining, construction, public safety, and defense. Specific examples of platform capabilities include vehicle-as-a-node, local inferencing (GPU/TPU), video/sensor analytics, safety interventions (driver fatigue/collision), and independent continuity (where operations continue despite disconnection).
Continue reading “Without Saying So Directly, Nokia Asserts its Right to Play in Physical AI”
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• Conversational AI is driving a major voice resurgence in customer service by improving the IP voice experience.
• Long call queues on account of human agents being thinly stretched across large call volumes have led to customer frustrations and poor CX, but modern versions of conversational AI are set to change that by taking away the frictions associated with voice.
It was believed that voice would diminish in value as digital channels started to emerge as an alternative to the voice channel. While messaging and chatbots offer cost and scale advantages, GlobalData’s research shows that voice continues to remain a vital channel for connecting with customers despite the frictions. Voice provides instant gratification and tends to be more straightforward to use as it does not involve navigating through messaging channels, websites and so and having to type messages. While the elderly demography tends to prefer voice due to greater familiarity, voice is seen to be popular even with the younger generation.
Continue reading “A New Breed of Conversational AI is Leading to Voice Resurgence in Customer Service”
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AI is changing the cloud landscape, creating the near-term need for a vast increase in processing power and storage space. Hyperscalers are responding with substantial facility construction plans. Just this year alone, Amazon Web Services, Google, and Microsoft Azure are pouring a total of $500 to $700 billion into extensions of their data center footprints. Given AI’s dominance in enterprise technology investment plans, this is a logical track. However, not everyone is on board with these aggressive development plans -and AI plays a role in that resistance.
Continue reading “Public Opposition to New Data Centers Disrupts but Doesn’t Derail US Facilities’ Expansion”Summary Bullets:
• After a period of ‘token maxxing,’ organizations are looking to reign in and better control inference costs.
• Instead, enterprises are now embracing ‘value-maxxing,’ which focuses on outcomes.
Last week, Google announced several enhancements to Gemini Enterprise designed to help enterprises obtain greater and faster ROI on their AI projects. The improvements address one of the biggest frustrations expressed by organizations today, namely that the benefits promised by AI are taking too long to realize. Companies are clamoring for domain specific solutions in order to speed the deployment, reduce the integration complexity, and increase the value obtained from AI projects. Additionally, business leaders are eager for better tools to help them manage AI costs. They are looking for improved visibility on token use and costs, more proactive spending controls, and more flexible payment options.
Continue reading “Google’s New Tools Support ‘Value Maxxing’ to Address Organizations’ Growing Concern Over AI ROI and Tokenomics”
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• Zayo will build 8,000 miles of new long-haul fiber across key AI corridors, with Nvidia becoming its anchor customer.
• Nvidia’s extends beyond GPUs and compute, with partnerships spanning the optical and networking ecosystem underpinning AI infrastructure.
Until now, the AI Infrastructure race has predominately been focused on GPUs, data centers and access to reliable power, yet beneath all three sits a less visible, but increasingly critical, layer – connectivity. As AI workloads become larger, more distributed and dependent on moving large volumes of data between locations, fiber is emerging as a fundamental component of the AI Stack. Zayo’s recent announcement to build 8,000 miles of new long-haul fiber across key AI corridors, backed by Nvidia as its anchor customer, could mark the new beginning of a new investment cycle for terrestrial networks. The bigger question is whether AI-related companies could become the anchor customer needed for the next generation of fiber investment?
Continue reading “AI Changing the Commercial Model for Fiber Build”
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