CRN has put together some of the biggest generative AI news stories to emerge so far in 2026 to help cut through the noise around AI and identify what solution providers need to focus on.
From artificial intelligence upstarts making early forays into the channel and enterprise sales to growing opportunities for solution providers in AI PCs and improving AI agent governance and observability, 2026 is seeing the AI market reach new heights and a new level of maturity as a lasting shift in how people work.
CRN has put together some of the biggest generative AI news stories to emerge so far in 2026 to help cut through the noise around AI and identify what solution providers need to focus on.
Sean Catlin, executive vice president and global head of strategy at Quebec-based Salesforce and AI solution provider OSF Digital, told CRN in a recent interview that OSF has been working with customers in a forward-deployed agentic motion that promises value in four weeks as part of its differentiation in the channel.
[RELATED: 2026 Year So Far]
Generative AI Trends 2026: What Solution Providers Need To Know
In OSF’s applied AI consulting approach, “you’re finding the use cases, you’re building real experiences, you’re not doing PowerPoints and Figma (presentations) and taking like 16 weeks to do strategy, but you’re actually live in the room with customers driving workshops (and) at the end of the workshop you’ve got a live, workable app and experience that is the real thing now,” Catlin said.
Generative AI is poised to be a $2.3 trillion market by 2032, Bloomberg Intelligence said in a report in June. That represents 22 percent of total technology spending across hardware, software, services and adjacent categories, with agentic systems moving from experimentation into scaled enterprise deployments. That also marks a $500 billion increase from BI’s prior forecast of $1.8 trillion published in March 2025.
BI attributed the increase to accelerating token consumption, the rapid expansion of coding and customer service agents plus a faster-than-anticipated shift in compute workloads from training to inference.
What follows are the biggest generative AI news stories of 2026 so far, ranked to the most important story unfolding. And be sure to check out CRN’s other 2026 Year So Far series, which includes articles on The 10 Coolest MSP Tools Of 2026 (So Far) and The 10 Hottest AI Security Startups Of 2026 (So Far).
10. AI Vendors Build Forward-Deployed Engineering Teams—Threat Or Opportunity?
One of the biggest emerging GenAI stories of 2026 is the forward-deployed engineering units multiple vendors have been announcing and investing in.
Vendors have portrayed these FDE units—modeled on an approach popularized by Palantir—as a way to assist with customer AI adoption and success. And while some vendors including Microsoft, Amazon Web Services, Google, Databricks and Salesforce have explicitly touted FDE arms as resources for solution providers, vendors will need to prove in the field that FDEs add to solution providers’ capabilities as opposed to cannibalizing their work.
Accenture’s 16 percent fall in stock price during the second quarter came in part due to AI model providers hiring more FDEs and building their own deployment arms, Morgan Stanley said in a June report. The investment firm still argued that IT services companies are still necessary for helping enterprises navigate multi-model strategies that fit with their complex IT environments and optimize AI token usage.
The vendors have put a staggering amount of investment behind these FDE units, with Microsoft pledging $2.5 billion for its Microsoft Frontier Co. and Amazon Web Services backing its FDE unit with $1 billion, for example.
Claude maker Anthropic and ChatGPT maker OpenAI even raised outside capital for their new in-house services arms. Anthropic’s AI services company has a total financial commitment of $1.5 billion, and the OpenAI Deployment Co. is backed by a $4 billion-plus initial investment and counts among its investors Capgemini–No. 4 on CRN’s 2025 Solution Provider 500–and fellow consulting and system integration giants Bain & Co. and McKinsey & Co. Both Anthropic and OpenAI reiterated support for their developing partner ecosystems even with the FDE investment.
FDEs are an emerging default execution layer for enterprise AI, but they could be a sign of AI’s immaturity and execution risk, investment firm Bernstein said in a June report. FDEs can accelerate time-to-value and unlock early monetization, but they show a lack of scalability.
Bernstein wants to see FDE efforts per customer fall as platforms mature. If headcounts grow as revenue grows, this is bad news for the AI industry and suggests lower margins for the technology than thought.
9. Neoclouds Surge As GPU Demand Creates New Channel Opportunities
As AI upstarts and startups invest in the channel, another new business type emerging in the AI era to show potential as a solution provider opportunity are neoclouds, a crop of cloud providers focused on providing access to graphics processing units as a service.
Neoclouds help increase solution providers’ capacity and enable GPU use for clients who can’t buy the chips for on-premises use or put them in the public cloud. Amsterdam-based Nebius, for example, has invested in channel partners to reach new markets and expand into the enterprise. It’s been developing a formal partner program with tiered incentives, AI training and education, as well as co-selling opportunities.
In April, Nebius worked with TD Synnex to reserve more than 1,000 high-end Nvidia GPUs in the cloud to help solution providers overcome supply constraints and get their customers moving on AI projects. The neocloud is open to replicating that partnership with other distributors, telecommunications companies, resellers and other business models.
Vultr, as another example, plans to launch a formalized channel program this year seeking to onboard about 100 different partners to start, with a focus on system integrators. CDW and Connection are among Vultr’s partners today. And neoclouds have proved an important partner to Nvidia’s ecosystem.
Synergy is forecasting that the neocloud market will reach $400 billion by 2031, representing a sustained 58 percent annual growth rate over the next five years.
Other neoclouds with partner programs include Armada, who counts Carahsoft among its solution providers. Lambda and DigitalOcean also have partner programs for resellers, MSPs and other partner business models.
8. AI PCs Head To Inflection Point As Adoption Accelerates
PC makers and solution providers selling devices have pointed to a coming inflection point for AI PCs as COVID-era PCs age out and interest around smaller AI models made inferencing at the device more of a possibility.
HP, for example, disclosed in May that AI PCs increased from more than 35 percent to 44 percent of shipment mix in the quarter. AI PCs need to make up roughly half of shipments for visible margin benefits, Bank of America said in a June report.
In April, IT distributor Ingram Micro said that AI PCs are about a quarter of its overall PC base and growing.
Improved AI PC pricing could help broaden demand, with a wider AI PC adoption potentially extending the device refresh cycle and smoothing some of the historical cyclicality of the traditional endpoint market, according to a William Blair report in June.
Gartner said worldwide PC shipments totaled 62.8 million units in the first quarter of 2026, up 4 percent year on year. However, the research firm attributed the increase to customers trying to get ahead of price hikes.
A report by International Data Corp. and sponsored by chip vendor Advanced Micro Devices (AMD) showed that 60 percent of organizations are piloting or have already deployed AI PCs–with 33 percent of organizations already piloting the devices. And 21 percent of organizations plan to deploy AI PCs within 12 months, the companies said in April.
New devices launched and coming to the market in 2026 include enterprise and commercial versions of Microsoft’s 13-inch Surface Pro and new Surface Laptop options with Qualcomm Snapdragon X2 processors, Lenovo’s seventh-generation ThinkPad X13 and ThinkPad L14, Dell Technologies’ 14-inch and 16-inch Pro 5 devices and Pro 14 Premium plus HP’s ZBook 8 G2i Intel-powered and G2a AMD-powered AI workstations and Z8 Fury G6i.
The Nvidia RTX Spark superchip announced in May is a potential catalyst for allowing AI agents to run locally on Windows devices, reducing the reliance on cloud computing and leading to a variety of equipment makers announcing products with the chip, Macquarie said in a report in June.
7. AI Drives Massive Infrastructure Spending
Partners with data center capabilities and AI expertise are experiencing strong growth as enterprises invest heavily in AI-ready infrastructure, according to research from CRN sister brand IPED. Channel Census research notes particularly strong momentum among enterprise-focused providers serving data center and infrastructure requirements.
The result is a channel environment where hardware decisions once again matter if for much of the cloud era, infrastructure became a background discussion.
AI chip giant Nvidia continues to see growing revenue, with rival AMD seeing increased central processing unit (CPU) demand from scaling AI workloads and even beleaguered Intel reporting benefits from the infrastructure boom.
In another example, Lenovo has seen growth in its AI-related category, which includes its flagship devices like PCs and smartphones with processing units, servers with graphics processing units, and services. And Dell Technologies has reported growth in AI-optimized servers.
The rush to embrace AI and digital transformation is resulting in demand for better ways to not only store data but manage it and make available without impacting its security.
Gartner estimated that worldwide spending on AI infrastructure alone in 2026 will reach $1.37 trillion, accounting for over 54 percent of total AI spending. That is up nearly 43 percent over spending in 2025 and is expected to grow another 28 percent in 2027.
6. Memory, Component Shortages Persist Amid Infrastructure Boom
AI in 2026 has really shown the dual nature of its opportunities and its constraints, prompting a surge in infrastructure spending while also causing shortages and price increases that continue to plague the channel.
In March, Hewlett Packard Enterprise CEO Antonio Neri told CRN that the memory supply crisis is a bigger problem than the supply constraints the industry faced during the global COVID-19 pandemic. The current memory crisis is complicated by the fact that there is also a technology transition to High Bandwidth Memory (HBM) version four.
In the second quarter, conventional dynamic random-access memory (DRAM) contract price increased 74 percent quarter to about $17.60 a gigabyte, according to a Bernstein report from July. The investment firm still expects the price increase to decelerate into the third quarter of 2026.
NAND contract price is expected to rise by about 60 percent quarter on quarter to about 25 cents per GB, with a narrower pace expected for the third quarter. Bernstein expects memory prices to gradually peak and begin to normalize from the second half of 2027 into 2028.
Solution providers have sought to help customers sidestep price increases and shipment delays while also facing unprecedented margin pressure as deals become more complicated and customers ask partners to absorb some of the extra cost.
At the same time, vendors are taking steps to protect themselves in ways that are impacting partners, rolling back long-standing terms that previously locked in order prices and canceling programs that safeguarded channel profits.
5. AI Security Risks Grow As Threat Actors Adopt Generative AI
In another example of the two sides to the AI coin, security vendors have leaned into AI innovation to ensure their products stay ahead of threat actors also adopting the technology to speed up and increase the volume of attacks.
Concerns over the security implications of Anthropic’s Claude Mythos 5 and Fable 5 even made mainstream news headlines this year after the U.S. applied export controls to the models in part due to security concerns. Anthropic redeployed and restored access to the models on July 1, according to the vendor.
From protecting sensitive data in AI applications to securing the activities of AI agents, a vast array of vendors in the cybersecurity industry have now expanded into the AI security space.
The widespread adoption of all manner of AI-powered tools for productivity has led to high demand for new products and capabilities from security vendors—especially those products that can reduce the risk of data breaches and other cyberattacks via the AI attack surface.
CrowdStrike, as an example of an AI-first, channel-heavy security vendor, has been making big strides to benefit partners through its access to the frontier models, which then carries through to partners via CrowdStrike’s Falcon platform. In another example, Snyk has invested in a new services delivery program for partners as the company seeks to help unlock massive AI security opportunities in the channel.
IPED research places security among the channel’s most important strategic investment areas alongside AI and networking. At the same time, security-focused content continues to rank among CRN’s strongest-performing editorial output, underscoring the market’s ongoing appetite for cybersecurity insight.
Alongside security vendor innovation through AI and investment in the channel, AI is accelerating threat actors and expanding the enterprise attack surface.
The average eCrime breakout time fell to 29 minutes in 2025, 65 percent faster than the prior year, according to CrowdStrike’s 2026 Global Threat Report published in February. The fastest observed breakout was in 27 seconds.
More than 90 organizations saw malicious prompt injections into GenAI tools, according to the report. And AI-enabled adversaries increased operations by 89 percent year on year, leveraging AI for reconnaissance, credential theft and evasion.
In April, Microsoft Defender Security Research detailed a widespread phishing campaign that uses the device code authentication flow to compromise organizational accounts at scale, moving away from static, manual scripts toward an AI-driven infrastructure and multiple automations end-to-end. Generative AI was used to create targeted phishing emails aligned to the victim’s role, as part of the campaign.
Even AI hype has proven a tool for threat actors, with Microsoft Threat Intelligence identifying a malicious Chromium-based extension that spoofs AI-powered answer engine Perplexity AI to trick unsuspecting users into installing it as an example.
4. AI Governance And Observability Become Critical
In an ongoing story that transcends security and extends the importance of networking and data platforms, customers are increasingly asking about AI governance, data exposure, compliance and operational risk, according to IPED data.
For solution providers, that shift creates significant opportunities in managed detection and response, compliance services, cyber resilience planning, recovery preparedness and security consulting. As customers race to adopt AI, security is becoming the guardrail that makes adoption possible.
As AI systems and applications proliferate, their need for data—lots of it—to complete their tasks is growing exponentially. AI agents, for example, require instant access to current, accurate data in order to effectively make autonomous decisions. Data management technology developers—and the solution providers they work with—play a key role in helping organizations collect, integrate, prepare and manage data for AI and agentic applications and the models that power them.
The data boom has driven some major acquisitions this year, with IBM completing its $11 billion purchase of real-time streaming data technology developer Confluent in March. And SAP bought master data management tech developer Reltio in May to help customers more effectively manage and prepare data for business analytics and AI tasks.
The need for modern data platforms and data cleansing and unification to get the best AI results has breathed new life into the market, with companies like Snowflake and Databricks seeing growth while the hyperscalers invest in their own data fabric offers.
Snowflake, for example, has seen its ecosystem explode to more than 14,200 global partners, up 22 percent year over year and 24 times the 600 partners Snowflake had in 2022. As CEO Sridhar Ramaswamy told CRN this year, “Our partners have always played a key role in helping realize the value of Snowflake, hence the growth.”
Databricks co-founder and CEO Ali Ghodsi predicts a 10-year boom in IT services demand by organizations that will need the channel’s help in preparing data and responsibly establishing artificial intelligence technology stacks, with the vendor’s solution providers telling CRN about how platform innovations are helping customers harden AI governance.
As far as hyperscalers building their own control planes for AI agents, one example is Microsoft’s Agent 365, which moved to general availability May 1, giving solution providers a single place for agent observations, governance, management and security across the organization. Without a unified control plane, IT teams might not have visibility into the number of agents, how they behave, who has access to them and security risks.
In two months, tens of millions of agents appeared in the Agent 365 Registry by preview customers, according to Microsoft. Cisco Systems’ acquisition of Galileo speaks to the agent observability and protection opportunity. And the ecosystems of security vendors like Zscaler and Okta have put forward those companies’ product portfolios as ways to address critical governance needs as agents proliferate. SentinelOne Co-founder and CEO Tomer Weingarten has even championed MSPs as “the hyperscalers for generative AI governance and security.”
“Identity absolutely is the perimeter at this point,” Rob Gregory, CISO at Denver-based Optiv, told CRN this year. “Agents in and of themselves are identities. And what they can do—or what they should be able to do—needs to be tracked, reviewed, attested to.”
3. New AI-Native Solution Providers Challenge The Status Quo
As the industry heads into year five of the ChatGPT AI era, the channel has seen an emergence of born-in-AI solution providers promising to reinvent the business or take it to a new level of efficiency.
Companies born after ChatGPT that are rewriting the book on IT services include MIPGlobal, Treeline, Ciridae and Hang Ten Systems. These companies’ pitches have garnered support from legendary technology investors, with those three raising more than $75 million from major investors including Andreessen Horowitz (a16z), Aramco Ventures and General Catalyst.
Meanwhile, more-established solution providers have told CRN that they don’t worry too much about born-in-AI services upstarts citing a similar argument to why traditional technology vendors aren’t so worried about AI vendor upstarts—the new guys lack the established relationships and decades of data under management as the established players.
The market may have room for both camps—or perhaps the channel will see a changing of the guard.
2. AI Reshapes Partner Pricing And Services Economics
The AI era means more solution providers are revisiting their own pricing models, with agents potentially eroding the billable-hours model some partners use.
In multiple CRN interviews this year with solution providers at the cutting edge of AI adoption, they have identified growing interest in outcome-based pricing as an interesting option for customers who want to see returns on their AI investments.
This economic evolution comes as research from CRN sister brand IPED points to the traditional distinction between reseller, systems integrator, consultant and MSP becoming increasingly blurred and recurring revenue now representing more than half of revenue across all major partner profiles. As pure-play resellers become increasingly uncommon, the channel may have another pricing evolution emerging.
As an example of the importance for solution providers to develop outcome-based models, Cognizant bought AI-first IT MSP Astreya Partners in June for about $600 million to add capabilities around data center buildouts with providers to adopt this new customer approach. CEO Ravi Kumar S said during the solution provider’s quarterly earnings call in April that Cognizant is shifting its economics from labor based to outcome based, with the solution provider looking to underwrite operational results for clients at scale instead of simply delivering projects.
Outcome-based pricing linking fees to savings or service improvements expands addressable markets and accelerate AI monetization, but it can introduce revenue variability and margin pressure during transition, Bernstein said in a June report. The firm predicts hybrid pricing models stabilizing revenues while increasing lifetime value and retention.
The firm believes that companies adopting a services-as-software model of software scalability meeting outcome-based pricing can see more than 30 percent growth on a small base while adding 5 to 10 percentage points to blended growth as adoption scales. Gross margins could reach as much as 70 percent with operating margins as much as 25 percent. Traditional services’ gross margins tend to reach 30 percent while operating margins tend to reach 15 percent. It predicts services-as-software reaching as much as $700 billion by 2028 and even $1.5 trillion longer term.
AWS, Google and other vendors are providing incentivesto solution providers to look at outcome-based approaches with customers. Anthropic’s partner program plans to add a performance-based incentive that will go live later this year aimed at Claude deployments that materially advance customer outcomes. And distributors like Pax8 and D&H Distributing have pledged to help partners move monetization models that support usage- and outcome-based services
In April, Microsoft CEO Satya Nadella told analysts on that month’s quarterly earnings call that the company is evolving beyond per-seat applications and consumption-based cloud infrastructure to an AI-era model combining the two—a model that could impact solution providers.
Nearly 60 percent of Microsoft customer service customers are already purchasing usage-based credits, Nadella said on the call. The Microsoft Copilot credit consumptive offer nearly doubled quarter over quarter as customers increasingly extend Copilot with custom agents tailored to their workflows. GitHub Copilot in June moved to a usage-based pricing model to align pricing to actual usage and costs, Nadella said.
1. OpenAI, Anthropic And AI Startups Expand Channel Programs
So far, the most exciting channel story unfolding in 2026 has to be the enterprise technology push by AI upstarts including Claude maker Anthropic and ChatGPT maker OpenAI.
Anthropic in March revealed a $100 million investment in its Claude Partner Network, new certification program and emerging partner organization of powerhouse channel executives from enterprise software vendors. Members of the Claude Partner Network include CRN Solution Provider 500 members Infosys, TCS, Accenture, Cognizant, Slalom, EPAM, Caylent and Leidos, as well as “born in the AI” services partner upstarts like Tribe AI and Ciridae.
In June, Anthropic expanded its channel push with a services track. The track already had more than 100 launch partners, with four tiers and a value construct for outcome-based business models.
OpenAI, meanwhile, officially kicks off its OpenAI Partner Network this month, backed by $150 million in funding. OpenAI’s inaugural partner program is a three-tier program with specializations, such as OpenAI Codex, that opens huge enterprise AI sales opportunities for skilled, AI-focused solution providers. The company’s goal is to train 300,000 certified OpenAI consultants by the end of 2026.
Although partners who have already officially signed up to the program are huge solution providers—such as Accenture, Boston Consulting Group and McKinsey—OpenAI is seeking highly skilled AI companies with successful AI track records.
Although Anthropic and OpenAI are among the hottest AI upstarts in the market due in part to plans of going public in the near future, other companies are also making compelling channel moves.
In February, Writer officially launched a new partner program for solution providers and transformation partners with sales and technical enablement resources, go-to-market toolkits, delivery frameworks and partner success support. Existing partners include Perficient and Cognizant. In May, TCS became French AI upstart Mistral’s first GSI partner to bring Forge to enterprises worldwide. Mistral also counts Accenture and Capgemini among its partners.
Perplexity added Tech Mahindra to its roster of services partners in June. San Francisco-based Devin AI maker and Windsurf owner Cognition disclosed in January partnerships with Cognizant and Infosys. Cognition also counts World Wide Technology among its solution provider partners. Toronto-based Cohere considers McKinsey, Accenture and Carahsoft members of its partner ecosystem.
While more conservative business customers of solution providers can bristle at unproven startups, the AI hype and opportunity for AI in the workplace is creating an evolving partnership between the most cutting-edge AI companies and the channel.
