2026 AI Predictions - Part 5

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 5, the final installment, covers AI's impacts on IT teams.

AI ROLE: CHIEF AGENT OFFICER

The Rise of the Chief AI Agent Officer: By 2026, enterprises will institutionalize AI accountability with a new executive seat: the Chief AI Agent Officer. This leader will define, audit, and govern the rules of engagement between humans and autonomous systems. Every AI action will be observable, explainable, and aligned with enterprise ethics. The organizations that adopt this role first will become the ones most trusted, proving that governance is not a brake on innovation but a moral accelerator.
Garth Fort
CPO, LogicMonitor

By the end of 2026, the "Head of AI" role will be table stakes for medium to large enterprises. In 2026, companies that still treat AI as the scattered side gig of three dozen people around the workforce will be signaling something uncomfortable: "We don't actually know what we're doing." Meanwhile, organizations that centralize AI leadership will look almost unfair by comparison. They'll be shipping faster, operating smarter, and treating AI less like a shiny new toy and more like an engine for reinventing how the company works.
Michael Domanic
Head of AI, UserTesting

AGENTIC COMMAND CENTER

Enter the Command Center: Organizations' adoption of AI in all its forms has advanced faster than their ability to govern, manage, and orchestrate it. The need for stronger oversight is only increasing as organizations deploy more agents and give them access to a wider range of core processes, demanding continuous, embedded visibility, and real-time control. A new approach is emerging to meet these challenges: the establishment of an operational layer that centralizes and integrates governance, control, and orchestration — an agentic command center. In 2026, organizations will devote significant time, energy, and investment to ensure their agentic operations have the governance frameworks and infrastructure needed to scale safely and effectively.
Raghu Malpani
CTO, UiPath

AI COUNCIL

As AI proliferates across industries and applications, it is becoming an increasing risk to enterprise security, privacy, and reputation. In 2026, enterprises will respond by creating cross-functional AI councils to define policies and standards, review new AI solutions, keep abreast of the rapid evolution of AI, and educate their workforce. These councils will bring together many perspectives, spanning compliance, security, legal, data science, IT, HR, and business to guide the business through this complex and rapidly evolving paradigm shift.  
Mitch Berk
Senior Director of Product Management, Omnissa

AI OPERATIONS STRATEGY

Every board will mandate an AI operations strategy — CIO agendas will shift from "whether" to "how fast" we deploy autonomous systems.
Ritu Dubey
Market Head, Digitate

AI QUALITY CONTROL

AI Quality Control Will Become a Core Enterprise Function: As the hype around building AI agents gives way to operational reality, the center of gravity will shift from creation to validation. By 2026, enterprises will stand up dedicated AI Quality Control (QC) functions — think of them as internal "AI Councils" — to ensure trust, consistency, and accountability. The old adage "garbage in, garbage out" now carries higher stakes. Poor data quality won't just skew dashboards; it will drive flawed decisions, erode customer trust, and hit revenue. QC teams will set the launch gates for AI agents, defining rigorous criteria for accuracy, consistency, and alignment with business goals. Anyone can ship an AI tool with a slick UI. The winners will be those who master the hard craft of making their AI correct. That's why AI Quality Control is poised to emerge as a core business function — embedding governance into the heart of enterprise AI.
Anahita Tafvizi
Chief Data and Analytics Officer, Snowflake

AI CHAMPION

The Year of the "AI Champion" Employee: 2026 will mark a turning point where AI stops being a technology story and becomes a people story. As AI agents continue to transform the workplace and introduce new security risks at every level, the real differentiator won't be who has simply deployed and integrated the most advanced AI tools — it'll be who's empowered their people with AI fluency to use them wisely and safely. The best companies will invest in developing the "AI champion" employee — someone who not only knows how to harness these systems responsibly, question their outputs, and innovate safely, but also sets the cultural standard for how it's applied across the organization. These AI-confident workforces are the ones that will define the next era of work.
Katya Laviolette
Chief People Officer, 1Password

AI ROLE: AGENTIC WORKFORCE MANAGER

The new middle manager is AI, guided by humans: By the end of 2026, AI will become the new middle manager, not in title, but in function. AI will handle the coordination load that once lived in the messy middle of many organizations, serving as the glue that keeps everything stitched together as companies grow flatter and faster. Organizations will begin putting AI directly onto the org chart, embedding digital coworkers inside every function to take on the grunt work while human leaders remain the ones making the calls that matter. This will also give rise to the Agentic Workforce Manager, as autonomous AI workforces take on more end-to-end work, and companies introduce roles focused on guiding, monitoring, and optimizing how agents operate. Humans will provide oversight while AI will eliminate delays, reduce miscommunication, and surface information instantly.
Dorit Zilbershot
Group VP, AI Experiences & Innovation, ServiceNow

AI ROLE: AI SYSTEMS ENGINEER

AI will collapse traditional role boundaries so completely that a new job category will emerge: the AI Systems Engineer. This role will subsume parts of software engineering, SRE, QA, data engineering, and product. The core skill will not be writing code, but framing problems, supervising agents, defining reward and constraint systems, and reasoning about complex socio-technical behavior end to end. Engineers previously trapped in firefighting and maintenance loops will find career leverage by becoming system-level reasoners who can translate intent into agent behavior and validate outcomes under uncertainty.
Sameer Agarwal
CTO, Deductive AI

AI ROLE: FORWARD DEPLOYED ENGINEER

The Forward Deployed Engineer Becomes the Hottest Job in Tech: The Forward Deployed Engineer is suddenly the most valuable person in your organization. Not your ML researchers, not your data scientists, the person who can actually make AI work inside your organization of legacy systems. These folks understand both worlds: they can wrangle a large language model and integrate it with your 20-year-old ERP system that nobody wants to touch. Here's why they're worth their weight in gold: every company has the same problem. You need AI to compete, but all your actual business runs on legacy infrastructure and software that predates the iPhone. FDEs are the only people who can bridge that gap, getting modern AI to play nice with Oracle databases, and whatever duct taped integrations your company's been running since the early 2000s. Compensation for good FDEs is about to skyrocket, and smart companies are already building internal programs to train them because you can't hire enough of them.
Jarrod Vawdrey
Field Chief Data Scientist, Domino Data Lab

AI ROLE: AI INTEGRATION ARCHITECT

In 2026, expect to see more AI integration architects who will be essential in embedding agentic workflows into enterprise systems.
Neeraj Abhyankar
VP, Data & AI, R Systems

WORKFORCE READINESS

Workforce Readiness Will be a Leading Indicator of AI ROI: The AI employee readiness crisis will evolve from a technical challenge to a cultural one. While 87% of business leaders believe AI will completely transform jobs within a year, only 31% say their workforce is ready to leverage it. This growing gap creates a "readiness paradox": one in which organizations are scaling technology faster than their people can absorb it. As this paradox deepens, leaders will begin to recognize that the real determinant of transformation success isn't tooling, it's trust. In fact, 42% of leaders cite building employee trust as a major obstacle to AI adoption. Companies can no longer rely solely on hiring or deploying new technology to stay ahead. Investment in change management, upskilling, and re-skilling will surge as leaders prioritize workforce readiness as the key lever for realizing AI ROI. The organizations that close the cultural gap, empowering employees to engage confidently with AI, will be the ones that capture its full potential. 
Dennis Perpetua
Global CTO Digital Workplace Services & Experience Officer, VP & Distinguished Engineer, Kyndryl

The biggest cost shift in 2026 won't come from switching vendors — it's realizing AI isn't a tool, it's a new workflow. Teams across functions are now expected to design and direct AI agents the way they once managed projects, constantly experimenting, refining prompts, and assembling lightweight systems that used to take full teams. Hiring prioritizes people fluent in this way of working because organizations no longer scale headcount to match the backlog — they scale agents. Humans focus on judgment and the nuanced calls machines can't make. In 2026, 2x productivity with AI is expected; the real question is whether you're building a culture where 100x feels achievable."
Ian Riopel
Co-Founder and CEO, Root

AI FLUENCY

Talent strategy becomes a tech strategy: AI fluency will become a core enterprise skill, not just knowing how to use AI, but how to prompt, govern, and collaborate with it effectively. The best teams won't just use AI; they'll orchestrate it.
Ha Hoang
CIO, Commvault

AI CULTURE

In the next wave of transformation, technology alone won't define AI leaders — culture will. The companies that win will make AI a trusted, accessible, and everyday capability for every employee, not a niche tool for specialists.
Marcelo Tamassia
Chief Technology Officer, Syntax

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OpenTelemetry: A Complete Telemetry Framework that Grows with You

Most organizations approach OpenTelemetry as a collection of individual tools they need to assemble from scratch. This view misses the bigger picture. OpenTelemetry is a complete telemetry framework with composable components that address specific problems at different stages of organizational maturity. You start with what you need today and adopt additional pieces as your observability practices evolve ...

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One of the earliest lessons I learned from architecting throughput-heavy services is that simplicity wins repeatedly: fewer moving parts, loosely coupled execution (fewer synchronous calls), and precise timing metering. You want data and decisions to travel the shortest possible path. The goal is to build a system where every strategy and each line of code (contention is the key metric) complements the decision trees ...

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Enterprise AI Reaches Pivotal Inflection Point: From Automation to Agentic Intelligence

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2026 AI Predictions - Part 5

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 5, the final installment, covers AI's impacts on IT teams.

AI ROLE: CHIEF AGENT OFFICER

The Rise of the Chief AI Agent Officer: By 2026, enterprises will institutionalize AI accountability with a new executive seat: the Chief AI Agent Officer. This leader will define, audit, and govern the rules of engagement between humans and autonomous systems. Every AI action will be observable, explainable, and aligned with enterprise ethics. The organizations that adopt this role first will become the ones most trusted, proving that governance is not a brake on innovation but a moral accelerator.
Garth Fort
CPO, LogicMonitor

By the end of 2026, the "Head of AI" role will be table stakes for medium to large enterprises. In 2026, companies that still treat AI as the scattered side gig of three dozen people around the workforce will be signaling something uncomfortable: "We don't actually know what we're doing." Meanwhile, organizations that centralize AI leadership will look almost unfair by comparison. They'll be shipping faster, operating smarter, and treating AI less like a shiny new toy and more like an engine for reinventing how the company works.
Michael Domanic
Head of AI, UserTesting

AGENTIC COMMAND CENTER

Enter the Command Center: Organizations' adoption of AI in all its forms has advanced faster than their ability to govern, manage, and orchestrate it. The need for stronger oversight is only increasing as organizations deploy more agents and give them access to a wider range of core processes, demanding continuous, embedded visibility, and real-time control. A new approach is emerging to meet these challenges: the establishment of an operational layer that centralizes and integrates governance, control, and orchestration — an agentic command center. In 2026, organizations will devote significant time, energy, and investment to ensure their agentic operations have the governance frameworks and infrastructure needed to scale safely and effectively.
Raghu Malpani
CTO, UiPath

AI COUNCIL

As AI proliferates across industries and applications, it is becoming an increasing risk to enterprise security, privacy, and reputation. In 2026, enterprises will respond by creating cross-functional AI councils to define policies and standards, review new AI solutions, keep abreast of the rapid evolution of AI, and educate their workforce. These councils will bring together many perspectives, spanning compliance, security, legal, data science, IT, HR, and business to guide the business through this complex and rapidly evolving paradigm shift.  
Mitch Berk
Senior Director of Product Management, Omnissa

AI OPERATIONS STRATEGY

Every board will mandate an AI operations strategy — CIO agendas will shift from "whether" to "how fast" we deploy autonomous systems.
Ritu Dubey
Market Head, Digitate

AI QUALITY CONTROL

AI Quality Control Will Become a Core Enterprise Function: As the hype around building AI agents gives way to operational reality, the center of gravity will shift from creation to validation. By 2026, enterprises will stand up dedicated AI Quality Control (QC) functions — think of them as internal "AI Councils" — to ensure trust, consistency, and accountability. The old adage "garbage in, garbage out" now carries higher stakes. Poor data quality won't just skew dashboards; it will drive flawed decisions, erode customer trust, and hit revenue. QC teams will set the launch gates for AI agents, defining rigorous criteria for accuracy, consistency, and alignment with business goals. Anyone can ship an AI tool with a slick UI. The winners will be those who master the hard craft of making their AI correct. That's why AI Quality Control is poised to emerge as a core business function — embedding governance into the heart of enterprise AI.
Anahita Tafvizi
Chief Data and Analytics Officer, Snowflake

AI CHAMPION

The Year of the "AI Champion" Employee: 2026 will mark a turning point where AI stops being a technology story and becomes a people story. As AI agents continue to transform the workplace and introduce new security risks at every level, the real differentiator won't be who has simply deployed and integrated the most advanced AI tools — it'll be who's empowered their people with AI fluency to use them wisely and safely. The best companies will invest in developing the "AI champion" employee — someone who not only knows how to harness these systems responsibly, question their outputs, and innovate safely, but also sets the cultural standard for how it's applied across the organization. These AI-confident workforces are the ones that will define the next era of work.
Katya Laviolette
Chief People Officer, 1Password

AI ROLE: AGENTIC WORKFORCE MANAGER

The new middle manager is AI, guided by humans: By the end of 2026, AI will become the new middle manager, not in title, but in function. AI will handle the coordination load that once lived in the messy middle of many organizations, serving as the glue that keeps everything stitched together as companies grow flatter and faster. Organizations will begin putting AI directly onto the org chart, embedding digital coworkers inside every function to take on the grunt work while human leaders remain the ones making the calls that matter. This will also give rise to the Agentic Workforce Manager, as autonomous AI workforces take on more end-to-end work, and companies introduce roles focused on guiding, monitoring, and optimizing how agents operate. Humans will provide oversight while AI will eliminate delays, reduce miscommunication, and surface information instantly.
Dorit Zilbershot
Group VP, AI Experiences & Innovation, ServiceNow

AI ROLE: AI SYSTEMS ENGINEER

AI will collapse traditional role boundaries so completely that a new job category will emerge: the AI Systems Engineer. This role will subsume parts of software engineering, SRE, QA, data engineering, and product. The core skill will not be writing code, but framing problems, supervising agents, defining reward and constraint systems, and reasoning about complex socio-technical behavior end to end. Engineers previously trapped in firefighting and maintenance loops will find career leverage by becoming system-level reasoners who can translate intent into agent behavior and validate outcomes under uncertainty.
Sameer Agarwal
CTO, Deductive AI

AI ROLE: FORWARD DEPLOYED ENGINEER

The Forward Deployed Engineer Becomes the Hottest Job in Tech: The Forward Deployed Engineer is suddenly the most valuable person in your organization. Not your ML researchers, not your data scientists, the person who can actually make AI work inside your organization of legacy systems. These folks understand both worlds: they can wrangle a large language model and integrate it with your 20-year-old ERP system that nobody wants to touch. Here's why they're worth their weight in gold: every company has the same problem. You need AI to compete, but all your actual business runs on legacy infrastructure and software that predates the iPhone. FDEs are the only people who can bridge that gap, getting modern AI to play nice with Oracle databases, and whatever duct taped integrations your company's been running since the early 2000s. Compensation for good FDEs is about to skyrocket, and smart companies are already building internal programs to train them because you can't hire enough of them.
Jarrod Vawdrey
Field Chief Data Scientist, Domino Data Lab

AI ROLE: AI INTEGRATION ARCHITECT

In 2026, expect to see more AI integration architects who will be essential in embedding agentic workflows into enterprise systems.
Neeraj Abhyankar
VP, Data & AI, R Systems

WORKFORCE READINESS

Workforce Readiness Will be a Leading Indicator of AI ROI: The AI employee readiness crisis will evolve from a technical challenge to a cultural one. While 87% of business leaders believe AI will completely transform jobs within a year, only 31% say their workforce is ready to leverage it. This growing gap creates a "readiness paradox": one in which organizations are scaling technology faster than their people can absorb it. As this paradox deepens, leaders will begin to recognize that the real determinant of transformation success isn't tooling, it's trust. In fact, 42% of leaders cite building employee trust as a major obstacle to AI adoption. Companies can no longer rely solely on hiring or deploying new technology to stay ahead. Investment in change management, upskilling, and re-skilling will surge as leaders prioritize workforce readiness as the key lever for realizing AI ROI. The organizations that close the cultural gap, empowering employees to engage confidently with AI, will be the ones that capture its full potential. 
Dennis Perpetua
Global CTO Digital Workplace Services & Experience Officer, VP & Distinguished Engineer, Kyndryl

The biggest cost shift in 2026 won't come from switching vendors — it's realizing AI isn't a tool, it's a new workflow. Teams across functions are now expected to design and direct AI agents the way they once managed projects, constantly experimenting, refining prompts, and assembling lightweight systems that used to take full teams. Hiring prioritizes people fluent in this way of working because organizations no longer scale headcount to match the backlog — they scale agents. Humans focus on judgment and the nuanced calls machines can't make. In 2026, 2x productivity with AI is expected; the real question is whether you're building a culture where 100x feels achievable."
Ian Riopel
Co-Founder and CEO, Root

AI FLUENCY

Talent strategy becomes a tech strategy: AI fluency will become a core enterprise skill, not just knowing how to use AI, but how to prompt, govern, and collaborate with it effectively. The best teams won't just use AI; they'll orchestrate it.
Ha Hoang
CIO, Commvault

AI CULTURE

In the next wave of transformation, technology alone won't define AI leaders — culture will. The companies that win will make AI a trusted, accessible, and everyday capability for every employee, not a niche tool for specialists.
Marcelo Tamassia
Chief Technology Officer, Syntax

Related Links

Hot Topics

The Latest

Crisis Communications: When the Outage Hits, Your Communications Can't Be "Investigating"

Outages aren't new. What's new is how quickly they spread across systems, vendors, regions and customer workflows. The moment that performance degrades, expectations escalate fast. In today's always-on environment, an outage isn't just a technical event. It's a trust event ...

OpenTelemetry: A Complete Telemetry Framework that Grows with You

Most organizations approach OpenTelemetry as a collection of individual tools they need to assemble from scratch. This view misses the bigger picture. OpenTelemetry is a complete telemetry framework with composable components that address specific problems at different stages of organizational maturity. You start with what you need today and adopt additional pieces as your observability practices evolve ...

The Quiet Power of Milliseconds in High Traffic Systems

One of the earliest lessons I learned from architecting throughput-heavy services is that simplicity wins repeatedly: fewer moving parts, loosely coupled execution (fewer synchronous calls), and precise timing metering. You want data and decisions to travel the shortest possible path. The goal is to build a system where every strategy and each line of code (contention is the key metric) complements the decision trees ...

Are AI "Autonomous Coworkers" Ready for Payroll?

As discussions around AI "autonomous coworkers" accelerate, many industry projections assume that agents will soon operate alongside human staff in making decisions, taking actions, and managing tasks with minimal oversight. But a growing number of critics (including some of the developers building these systems) argue that the industry still has a long way to go to be able to treat AI agents like fully trusted teammates ...

Enterprise AI Reaches Pivotal Inflection Point: From Automation to Agentic Intelligence

Enterprise AI has entered a transformational phase where, according to Digitate's recently released survey, Agentic AI and the Future of Enterprise IT, companies are moving beyond traditional automation toward Agentic AI systems designed to reason, adapt, and collaborate alongside human teams ...