As enterprises and channel partners move beyond AI experimentation, 2026 is emerging as a pivotal year for how artificial intelligence is deployed and measured.
From the rise of agentic AI and new AI-focused roles to growing ROI pressure, security concerns, and regulation, industry leaders say AI will become a core operational and budget priority across the IT channel.
What AI technologies will matter most to the IT channel in 2026
With the past year bringing a steady stream of AI developments, 2026 looks to be no different. One of the biggest shifts this 2025 has been the rise of agentic AI — systems designed to do more than generate content and instead take action across workflows.
Structured founder and CEO Daniel Nissan expects 2026 to mark a sharp transition from generative AI to agentic AI, predicting that these tools will begin playing a more concrete role in partner enablement teams and other essential parts of an organization.
“The conversation is no longer about GenAI drafting copy. It’s about Agentic AI acting like a team member. These systems will research, recommend, and execute on partner tasks like MDF planning, campaign deployment, and reporting,” Nissan said.
Nissan also cited a recent Ernst & Young survey that found nearly 50 percent of tech leaders are already deploying autonomous AI, and he expects it to account for the majority of their AI stack within 24 months.
R Systems VP for Data & AI Neeraj Abhyankar echoed that view, framing the next AI evolution as the ‘AI Workforce of the Future.’
“The next phase of AI transformation will hinge on specialized roles as AI evolves from a tool into autonomous agents acting as digital co-workers with defined responsibilities and KPIs,” Abhyankar said. “In 2026, expect to see more AI integration architects who will be essential in embedding agentic workflows into enterprise systems.”
He named roles such as governance and ethics leads responsible for real-time compliance, along with prompt engineers and LLM Ops specialists, as positions that will only grow in importance as enterprise AI adoption matures.
Meanwhile, experts from West Monroe offer a more foundational perspective on upcoming AI innovations. In their 2026 Software Outlook report, they argue that AI-ready data foundations will determine whether AI projects succeed or stall, especially as organizations navigate the balancing act between data access for AI performance and data privacy.
“60 percent of AI projects fail because they lack AI-ready data foundations. The most successful software companies are deeply understanding what makes their data unique, securing clear rights of use, and building strong data architectures that unlock AI’s full potential.”
“Proprietary data is becoming the true differentiator — not access to the latest models,” West Monroe added.
How enterprises will measure AI ROI in 2026
Tech leaders also expect AI to command a bigger share of IT budgets in 2026, intensifying competition among software vendors fighting for wallet share.
West Monroe found that AI now accounts for 12 to 15 percent of enterprise IT budgets, underscoring AI’s growing pull on organizations’ budget priorities, particularly as the technology matures and expectations rise alongside it.
“The shift from seat-based SaaS to agent-first, outcome-driven experiences is changing how value gets priced and delivered. Companies with a clear AI roadmap and early customer proof points will defend their position — those without risk losing ground fast.”
How competitive advantage can be built in industries from healthcare to retail
In this shift in IT budgets, Abhyankar emphasized that businesses can gain a competitive advantage with their AI investments if they prioritize four critical areas:
- Agentic AI platforms that enable multi-agent orchestration.
- AI-native infrastructures built for scale, security, and interoperability.
- Data modernization tools that unlock the full potential of unstructured data.
- AI observability and safety tools that monitor, govern, and refine agent behavior in real time.
“These strategic investments will fuel the next wave of business impact as AI agents drive hyper-personalized experiences and new levels of operational efficiency,” Abhyankar said.
Abhyankar highlighted the following industries that have optimized their product offerings and workflows with AI:
- Healthcare: Diagnostics and personalized care
- Financial services: Autonomous compliance and fraud detection
- Retail: Product discovery and inventory optimization
- Manufacturing: Predictive maintenance and smart robotics
Google’s ROI study results linger as companies consider AI spend next year
Meanwhile, the West Monroe report also underscored that success will be measured by ROI, not just innovation. Earlier this year, we covered Google Cloud’s ROI of AI 2025 report, which specifically explored whether AI innovations were delivering measurable business impact across enterprises.
Google surveyed roughly 3,466 senior enterprise leaders worldwide, including C-suite executives and IT decision-makers from CEOs to IT directors.
In the report, Google identified five areas where organizations are seeing measurable AI ROI:
- Productivity: 70 percent reported increased productivity from AI (71 percent in 2024). Notably, 39 percent saw ROI from GenAI use cases supporting individual work, such as drafting emails, presentations, and documents.
- Customer experience: 63 percent reported an improved customer experience by using AI as an engine for user engagement (60 percent in 2024).
- Business growth: 56 percent of organizations reported higher revenue growth when leveraging AI in production (63 percent in 2024).
- Marketing: 55 percent reported a meaningful impact on marketing workflows and campaigns (a new finding introduced in 2025).
- Security: 49 percent reported improvements to their organization’s overall security posture (56 percent in 2024).
While progress will continue across these areas, AI ROI will increasingly be evaluated alongside two pressures: AI regulation and the security implications of deploying AI at scale.
Why AI governance and assurance become table stakes
2026 is expected to be a pivotal year for AI regulation, particularly in how organizations handle compliance and governance. That applies to both companies adopting AI internally and vendors building and selling AI-powered products and services.
Alexis Kateifides, director for regulatory intelligence enablement at OneTrust, argued that AI regulation is increasingly shaping how innovation earns trust, and that governance frameworks are starting to translate into measurable returns.
“AI regulation is defining how innovation earns trust. For organizations, these laws are becoming the foundation of responsible growth, guiding how technology is designed, deployed, and governed. The next phase of governance is about pace and precision,” Kateifides said.
“The combined efforts of compliance, privacy, and risk teams are delivering measurable value as frameworks to govern AI crystallize. What began as regulatory readiness is now translating into business performance and stronger returns on investment,” he continued.
Avani Desai, CEO of attestation and compliance services provider Schellman, shared a similar view, predicting the conversation will shift from AI adoption to AI assurance and trustworthiness.
“As ‘responsible AI’ becomes a global headline, the risk of shallow claims grows. Independent assurance will become the key differentiator between marketing and reality. Organizations will need to demonstrate, not just declare, that their AI systems are governed, tested, and monitored. Third-party verification will validate that model inventories are complete, controls are effective, and oversight is active,” said Desai.
“This evidence will provide boards with defensible confidence and give regulators and customers tangible proof of trustworthiness. Over time, AI assurance will resemble financial and cybersecurity audits, complete with independent standards, external testing, and transparent reporting.”
The security angle: from AI-driven threats to AI-first incident response
Josh Taylor, lead security analyst at Fortra, expects AI to reshape security on two fronts: empowering threat actors and raising new liability questions when AI systems cause measurable harm.
“Threat actors will deploy AI to craft adaptive, scalable, and personalized attacks that bypass static defenses and exploit human trust. Enterprises must counter this with dynamic, behavior-based security models and prepare for threats that learn and evolve in real time,” Taylor said.
He also predicts enterprises will begin treating AI systems as “insider threats,” citing the expansive access these services require and the risks that come with it.
“AI agents need cross-functional access to be useful, they operate 24/7, and they make thousands of decisions per day that no human reviews. The first time an AI agent gets compromised through prompt injection or a supply chain attack and starts quietly exfiltrating customer data under the guise of ‘helping users,’ organizations will realize they built privileged access with no monitoring.”
Taylor expects the first half of 2026 to bring the first “AI lawsuit,” creating an inflection point over liability when AI causes measurable harm — such as leaking confidential information, violating regulations, or making unfulfilled commitments.
“A lawsuit will likely involve an AI agent that had access to privileged information and disclosed it inappropriately, or an AI assistant that shares proprietary data.
“This will force the industry to answer questions nobody wants to ask: Who is liable when an AI you gave permission to act on your behalf and does something harmful? The vendor? The company? The AI itself?”
At the same time, Fortra Chief Strategy Officer John Grancarich believes AI will increasingly augment SOCs, helping them operate as an organization’s first line of defense.
“By 2026, AI will evolve into the first responder for cyber defense teams,” Grancarich said.
“We’re quickly entering an era where AI will handle the majority of incident triage and containment in seconds, allowing human defenders to focus on strategy, attack forensics and threat hunting.”
Bottom line: With AI moving fast, we have to do our best to keep up
In my view, the speed of change driven by AI makes the predictions discussed above all the more critical. AI, agentic AI, generative AI, and all the other emerging AI technologies have the potential to reshape the IT channel in an instant — and we’ve seen it firsthand.
In just three years, we have gone from ChatGPT being a nice party trick to nearly every business, vendor, and customer actively deploying AI across their operations.
To be clear, no one can fully predict where AI is headed. But the responsible move is to plan for the most likely outcomes: enable innovation without compromising security, equip teams with the AI expertise they’ll need, and put safeguards in place to protect sensitive data.
If we do that well, we’ll hopefully get to a point where AI consistently drives real ROI and meaningful gains across the business, rather than becoming just another tagline riding the trend.
Key takeaways
- Agentic AI moves into real-world operations: In 2026, AI will shift from generative tools to autonomous agents that execute workflows, support partners, and act as digital co-workers across the IT channel.
- AI ROI becomes the defining metric: Enterprises will judge AI success by measurable business impact—productivity, revenue growth, security improvements, and operational efficiency.
- Data and governance drive competitive advantage: Strong data foundations, compliance frameworks, and AI assurance will separate trusted vendors from those struggling to scale responsibly.
- Security and accountability take center stage: As AI-driven threats grow, organizations will adopt AI-first incident response while confronting new questions around risk, liability, and oversight.
For a look back at what IT leaders said they wanted most from solution providers in 2025, and whether those expectations were met, check out our recap: What Top Technologies IT Leaders Want From Solution Providers in 2025.
