IT Connection

Agentic AI Transforms the Marketplace UX as Infra Services Become Consumable Products

October 6, 2026October 6, 2026 by Charlotte Dunlap, posted in Big Data

Agentic AI Transforms the Marketplace UX as Infra Services Become Consumable Products

Close-up portrait of a smiling woman with blonde hair and earrings, in a softly lit setting. — C. Dunlap
Research Director

Summary Bullets:

• 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.

Struggling for years on trying to fit a square peg into a round hole, telcos are recognizing the online storefronts as a prime route to sales growth by leveraging agentic AI to streamline enterprise delivery of network services. Factors range from agentic AI-driven product procurement through conversational discovery of solutions, to improved productization of infrastructure services.

Advancements in open-source software (OSS) have resulted in a greater number of carrier solutions being listed on marketplaces, alongside standardized APIs (enabled through MCPs, GSMA Open Gateway, and CAMARA) for streamlined connectivity. Networks (e.g., networks-as-code) are evolving and becoming more consumable and programmable via enterprise agents, with no complex coding or integration required by enterprises. Ericsson-led network-API operator alliance, Aduna, is a good example of such activities. Nokia’s contribution of Network-as-Code APIs to Google Cloud Marketplace is another.

Telcos are filling key roles through marketplace channels, including fulfilling private wireless deals, reselling software and platform services, and offering enterprise customers valuable consulting and integration services.

This infra productization couples nicely with another trend in marketplaces: Agent mode UX innovations have appeared across marketplaces. They support conversational discovery experiences for software procurement and are significant for their role in broadening the audience of less technical buyers.

Within the last year, AWS released two AI-powered tools for its marketplace: agent mode, which is its version of a conversational discovery experience for software procurement; and enhanced search. Buyers describe to the agent a use case, including specific requirements, to gather product details and compare options. These conversational queries in marketplaces are significant to sellers for their role in expanding the audience to include less technical buyers looking to solve their companies’ digitization issues.

Google and Microsoft also released chat-style methods to discover appropriate solutions on marketplaces. Google’s AI-powered search experience moves beyond keyword searches to provide users with natural-language discovery across its services and AI agent catalog. Its approach is similar to AWS by allowing users to describe their goals or a technical problem in order to better identify appropriate products, including third-party offerings. Microsoft brands its conversational AI experience as ‘intelligent discovery’, with interactive chat-enabled evaluation and comparisons of products.

A lot is at stake in the battle of the hyperscaler marketplaces, reported to be worth tens of billions of dollars, including partner solutions. AWS now claims over 30,000 product listings, including an AI Agents and Tools category launched last July and later that year, and agent mode for AI-enhanced search for buyers. Microsoft rebuilt its marketplace last September after merging its Azure Marketplace and AppSource. The storefront now includes over 3,000 AI apps and agents. Adding AI Agent Marketplace last year, Google differentiates on a cost basis, cutting its fee from a flat 3% down to 1.5% for certain deals. The marketplace wars will heat up as the telcos increasingly play in this space.

Chinese Cloud Giants Close Enterprise AI Platform Gap with Global Hyperscalers, but Execution Lags

October 6, 2026October 6, 2026 by Alfie Amir, posted in IT Leader

A smiling man in a formal suit and red tie, set against a white background. — A. Amir

Summary Bullets:

• Chinese providers are catching up with global leaders in three areas: generative AI, operationalized solutions, and agentic AI, giving enterprises broader options to diversify their AI partners.

• However, gaps in go-to-market, professional services, and model development remain large – crucial areas to drive adoption and accelerate deployments.

AI demand continues to grow rapidly. GlobalData Market Opportunity Forecasts to 2030: Artificial Intelligence (published on June 30, 2026) forecasts the global AI market to increase at 48.2% five-year-CAGR to reach $1.3 trillion in 2030. This is also reflected by 88% of the 3,069 global enterprises interviewed by GlobalData, who increased their AI budget this year (source: GlobalData ICT Customer Insights Survey 2026. Asia-Pacific shows a similar trend with a 48.6% CAGR, accounting for 36.2% of the global AI market in 2026. While growth is reported across the stack from the GPU to the application layer, cloud-based enterprise platforms remain crucial to drive adoption by providing broad and flexible capabilities to develop, govern, and scale AI deployments. GlobalData’s recent updates on Cloud-Based Enterprise AI Platforms: Competitive Landscape Assessment (September 17, 2026) shows that global hyperscalers (Google and Amazon) continue to lead the market, followed closely by Microsoft and IBM. However, Chinese players including Alibaba, Baidu, Huawei, and Tencent are closing the gap. This is important especially in markets like Asia where these players already have a strong presence. This gives enterprises broader options to diversify their AI partners, but also attracts cost-sensitive customers through their cost-leadership strategy.

The Competitive Landscape Assessment report also analyzes vendors’ capabilities, competitive comparison, market assessment, market drivers, buying criteria, and vendor recommendations. It covers 10 vendors: Alibaba, Amazon, Baidu, Dataiku, DataRobot, Google, Huawei, IBM, Microsoft, and Tencent Cloud.

Gaps Getting Smaller

Chinese providers are catching up with global leaders in three areas: generative AI (GenAI), operationalized solutions, and agentic AI. In the report, Alibaba is rated Very Strong in GenAI, the same as Amazon and one level behind the leader, Google. Alibaba’s latest Qwen family lets users toggle reasoning on and off, supports over 200 languages and dialects, and includes the agent-focused Qwen3.7-Max. Meanwhile, Baidu, Huawei, and Tencent are rated Strong. Baidu’s ERNIE 5.1 and Qianfan platform combine in-house models with DeepSeek, Kimi, and GLM. Tencent’s Hunyuan 3D and video models have over 3 million Hugging Face downloads, and Huawei has open-sourced a version of Pangu as OpenPangu.

Operationalized solutions are the clearest convergence. Alibaba and Huawei are both rated Very Strong, matching Amazon and ahead of several others. Alibaba offers vertical portfolios in finance, education, transportation, and retail while Huawei supports over 400 prepackaged AI applications across 500 industrial scenarios. Rated Strong, Tencent’s Productivity Agent Suite spans more than 20 verticals. Tencent is also extending into physical AI with its Hy-Embodied models, Tairos platform, and Unitree partnership, although deployments remain early. Industry-specific solutions are becoming more important for enterprises exploring the technologies as well as when moving from PoC to production.

The gap in agentic AI is closing more slowly. Alibaba, Baidu, and Tencent are rated Strong while Huawei is Competitive. Alibaba offers AgentRun, AgentTeams, and Agent Sandbox. Alibaba also offers a Skills portal, which converts cloud capabilities into MCP-compatible formats. Tencent has ADP 4.0 which is compatible with OpenAI’s Agents SDK) while Huawei offers AgentArts and AgentSphere. This shows not only serious investment by these players, but also increasing initiatives to support open standards rather than build closed ecosystems. However, their development platforms and tooling are rather new and less proven compared to global players.

This growing momentum is underpinned by their vertical integration strategies with investment in infrastructure such as Huawei’s Ascend 950 chips, the 1,024-card Atlas 950 SuperPod, Alibaba’s Zhenwu M890, and Baidu’s Kunlun chips. This is also reflected in their financial performance. Huawei reported $7.5 billion in AI chip revenue, Alibaba claimed 11 consecutive quarters of triple-digit AI revenue growth and over 290,000 GenAI customers, and Tencent said its AI cloud revenue doubles every year.

Where Gaps Remain

The widest gap is go-to-market. Alibaba, Baidu, Huawei, and Tencent are all rated only Competitive. While they have a strong presence in China supported by various references, their global footprints are relatively small: Alibaba has 32 regions in 17 countries, Huawei 34 in 16, and Tencent 21 in 10. All four have a predominantly Asia-centric or China-centric customer base. Geopolitical headwinds are a structural constraint, particularly in North America and Western Europe.

Another key area is professional services. Rated Competitive, these players still lack professional and managed services as well as partner ecosystem, which is crucial in helping enterprises with deployments, but also lag in ethical and governance frameworks. IBM’s 21,000 data and AI consultants and Google’s ecosystem of over 220,000 GenAI-enabled partner consultants set the benchmark.

The third is model development. Chinese providers have end-to-end tooling, such as Alibaba’s PAI, Huawei’s ModelArts, and Tencent’s TI Platform, but the experience is less unified. Tencent’s tooling, for example, is fragmented across TI Platform, ADP, and TokenHub. Global players are also ahead in the governance and monitoring tools that enterprises need to move from PoC to production.

Systems Integrators Adopting the FDE Model with a Focus on Business Outcomes

September 29, 2026September 29, 2026 by siowmeng, posted in Big Data, Cloud Enable, Secure

A professional man with dark hair and a slight smile, wearing a suit jacket over a light blue shirt, standing in front of a blurred glass background. — S. Soh

Summary Bullets:

• 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).

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Agentic AI May Give IP Voice a New Lease on Life as Legacy Decline Continues

September 29, 2026September 29, 2026 by Gary Barton, posted in Big Data

Gary Barton – Research Director, Enterprise Technology and Services

Summary Bullets:

• 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.

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Meta Will Need to Shed its Consumer-centric Image to Gain Ground in Enterprise AI

September 29, 2026September 30, 2026 by Rena Bhattacharyya, posted in Big Data

A woman with long, dark hair wearing a gray blazer, smiling at the camera. — R. Bhattacharyya

Summary Bullets:

• 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.

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Australia’s Cable Wars Are Heating Up: Thanks, AI

September 28, 2026September 29, 2026 by Brendan Swan, posted in Network

B. Swan

• Artificial intelligence (AI) is reshaping Australia’s fiber map, driving investment beyond city limits and into emerging data center locations.

• Route diversity is becoming strategic, with terrestrial and subsea network providing greater resilience and flexibility for future digital workloads.

Australia’s fiber build-out is getting a second wind – and this time, artificial intelligence (AI) is changing the rules of the game. In the same week, Vocus and SUBCO announced new terrestrial and subsea cable projects demonstrating that Australia’s connectivity investment cycle is picking up speed. But this is about more than adding fiber. AI, cloud and data center expansions are changing where capacity is required and creating demand for networks with diverse, resilient routes that can withstand outages, congestion and other disruptions.

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Google is Keeping Workspace on the Cutting Edge

September 25, 2026September 30, 2026 by Gregg Willsky, posted in Big Data, Communicate

G. Willsky

Summary Bullets:

• 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.

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Beyond the Hype: The Reality of CX Agentic Orchestration

September 24, 2026September 24, 2026 by orumohiuddin, posted in Cloud Enable, Communicate, Secure

A woman with long dark hair wearing a colorful patterned top and a pearl necklace, smiling softly at the camera. — Oru Mohiuddin

Summary Bullets:

• Agentic orchestration has been dominating vendor narratives as growing complexity in the CX space is driving the need for a sophisticated coordination system.

• CX agentic orchestration remains fragmented as there are still infrastructural gaps, and trust remains a major issue for customers.

Agentic orchestration has been increasingly occupying CX vendor narratives in recent years, so it is time to take a deep dive into what orchestration is and why it is becoming relevant. Simply put, orchestration is bringing people, workflows, and technology together to achieve an outcome. Depending on how far we stretch the concept, orchestration is not new, and even a deterministic call routing can be described as orchestration. The question is, what is new today and why is orchestration increasingly dominating vendor narratives?

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Salesforce Dreamforce 2026: Salesforce Combats AI Mistrust via Control Plane

September 23, 2026September 23, 2026 by Charlotte Dunlap, posted in Cloud Enable

Close-up portrait of a smiling woman with blonde hair and earrings, against a blurred background. — C. Dunlap
Research Director

Summary Bullets:

• New fears of AI breaches and vulnerabilities significantly threaten AI adoption

• Salesforce and rivals launch aggressive control plane portfolios as part of the new layer of the AI stack

On the heels of broad industry doomsday reports of AIs going rogue, Salesforce launched its mega Dreamforce conference in San Francisco, California (US) last week. CEO Marc Benioff used the stage to reposition the company as the industry platform to provide the oversight and governance of both Salesforce and third-party agents under a single view.

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Under Pressure to Demonstrate AI ROI, Too Often Organizations Come Up Short

September 22, 2026September 22, 2026 by Amy Larsen DeCarlo, posted in IT Leader

Close-up portrait of a woman with blonde hair, wearing a black jacket and light-colored sweater. — Amy Larsen DeCarlo – Principal Analyst, Security and Data Center Services

Summary Bullets:

• Concerns about missing the AI boat have many corporate executives pushing AI application development mandates.

• However, research indicates that far too few organizations are realizing the kind of expected dividends in terms of cost savings, revenue generation, productivity gains, and innovation. What can they do differently to make the most of their investments?

To say artificial intelligence (AI) has become ubiquitous is almost an understatement. Just under 90% of all enterprises today use AI to support at least one corporate function, according to consulting firm McKinsey and Company, with 56% of all organizations applying the technology across three or more discrete tasks. This pace of adoption is unprecedented. Stanford University’s 2026 AI Index Report says 53% of the global population had been using generative AI (GenAI) within three years of widespread availability. For comparison’s sake, it was 12 years before the personal computer reached 40% of the population.

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