As artificial intelligence shifts from experimentation to everyday execution, organizations are beginning to recognize that success hinges less on the technology itself and more on how prepared their people and processes are to use it. From upskilling teams to redefining workflows and governance, AI readiness is quickly becoming a strategic priority.
The following perspectives highlight why 2026 will be a pivotal year for AI-focused training, consulting, and organizational change as businesses work to turn AI potential into real, sustainable impact. Read on to learn more about what companies in AI and adjacent industries have to say.
AI-readiness Initiatives, Trainings & Consulting
In Gartner’s recent report on AI, they state that “AI will touch nearly all IT work by 2030”. Despite this, they actually foresee AI creating more job and workloads than it will replace as 75% of the work will be done by humans using AI tools versus exclusively completed by AI alone. What this means for businesses, is they will have a major undertaking in store to prepare teams for how best to use these incoming new AI-powered toolsets. Expect 2026 to be filled with AI-readiness initiatives, AI training, and business consulting on how best to leverage increased efficiencies powered by AI.
Colton De Vos, Marketing Specialist, Resolute Technology Solutions
Enhanced AI Trading Precision and Efficiency
AI by 2026 will likely deepen its role in enhancing trading precision and efficiency. We’re going to see advanced predictive algorithms that not only analyze data faster but adapt dynamically to market changes in real-time. This evolution will empower traders to make decisions with a level of confidence and speed that was almost unattainable before.
With my focus on maintaining secure, high-performance infrastructures, I see the integration of AI making trading environments smarter and more resilient, especially in managing market volatility. Secure deployment and trust in AI systems will be the foundation of success in this space, and those who invest in reliable frameworks now will reap the rewards as new AI capabilities emerge.
Ace Zhuo, CEO, Sales and Marketing, Tech & Finance Expert, TradingFXVPS
Success Will Come From Embedding AI Into Core Processes
Drawing on over a decade of experience guiding businesses in adopting AI solutions, I’ve observed firsthand how tailored implementations outperform generic approaches. Companies that focus on niche-specific AI applications, such as sentiment analysis to enhance customer service or predictive maintenance in manufacturing, achieve faster ROI and sustainable growth. Success lies not just in using AI but in strategically embedding it into core processes with measurable objectives. This perspective stems directly from consulting with enterprises transitioning from static processes to agile, AI-driven ecosystems.
Valentin Radu, CEO & Founder, Omniconvert
A Growing Need for Effective AI Governance Will Increase SDD
Spec-Driven Development (SDD) is expected to continue gaining traction in 2026, largely due to the growing need for effective governance and guidance of AI Agents across both ends of the DevOps spectrum. New standards such as Spec Kit will serve as authoritative references for design, task management and workflow execution, enabling teams made up of AI Agents and humans to speed up product release cycles. DevOps tools will adapt in support of this transformation, enabling Agentic workflows via standards such as the Model Context Protocol (MCP). With machine-readable artifacts (specs) as the ground truth, code & infrastructure generation becomes more deterministic and consistent. SDD offers a shared language — usable by developers, operations, security, and AI tooling — to align across concerns.
Steve Tranchida, VP, Architecture and Strategy, Verinext
Agentic Mesh Across Clinical, Business, and Edge
Today’s point-solution automations will evolve into an agentic mesh spanning EMR, ERP, contact center, IoT, and patient-facing channels. Digital IT professionals will architect “care and ops fabrics” where specialized agents coordinate—monitoring elderly patients, preparing oncology visits, optimizing OR schedules, and orchestrating revenue cycle—while IT manages standards, routing, and safety between them.
Howard Rosen, CEO, Nova Insights
Gamification of AI Engagement
Here’s the thing about AI in commerce, I think the real shift is in gamification. We’re using AI to change game rules based on how people actually click and buy, and suddenly more people are playing along. Personalization isn’t a buzzword anymore, it’s just what shoppers expect. My advice is to start testing small AI engagement ideas now. The brands that move fast are going to win.
John Cheng, CEO, PlayAbly.AI
Continuously Learning Decision-Support Systems
In 2026, the most effective use of AI in startups will be decision-support systems that learn continuously from customer activity, market trends, and internal performance to guide product development and recruiting. The priority will be integrating these tools into daily workflows so teams make faster, clearer decisions without replacing human judgment.
George Fironov, Co-Founder & CEO, Talmatic
The Rise of Micro-AI Workflows
People won’t rely on one massive system for everything. Instead, they’ll string together small, specialized models that quietly automate the tiny decisions we make all day—things we’re barely conscious of but that steal hours from our schedule. The companies leaning into this today are already seeing compounding gains.
Max Shak, Founder/CEO, nerD AI
AI Stops Being a Playground
I’m seeing 2026 turn into the moment when AI stops being a playground and starts being something organizations are held accountable for. The questions I’m getting now aren’t about clever prompts or flashy demos–they’re about cost, reliability, audit trails, and what happens when a model behaves unpredictably. AI isn’t pushing engineers out of the picture; it’s becoming another dependency we have to secure, test, and monitor like any other piece of critical infrastructure.
A recent project of ours used Azure Cognitive Services to handle support-ticket triage. It automates about 80 percent of the workflow, but it only works because it’s wrapped in guardrails, fallback paths, and tight logging. That’s the direction I expect AI to go: narrow, well-defined responsibilities inside larger, more deterministic systems, treated like any other service with real SLAs attached.
Igor Golovko, Developer, Founder, TwinCore
Identity Security: Identity-based Attacks Will Dominate CISO Investments
AI Comes to Thin Clients
In 2026 businesses will start to look at thin clients as a means of efficiently delivering AI workloads, whether through VDI or DaaS. Thin clients can move AI workloads to a server or the cloud, saving businesses the need to replace existing hardware. The costly alternative is running AI locally and having to purchase new hardware. From the sustainability perspective, thin clients consume less footprint than new hardware built for AI, another benefit.
Stuart Pladgeman, VP Sales, 10ZiG
AI Tools That Work Alongside Creators
AI is changing the game in creative media. On our platform, it helps creators find their audience, and I’ve seen it firsthand with some sports media teams we work with. The matching system was clunky at first, but now it’s much more on point. For 2026, I’m excited to try more AI tools that work alongside creators. The way they help people turn creative ideas into reality is pretty cool.
Runbo Li, CEO, Magic Hour
Companies Will Adopt Practical Guardrails
By 2026, most engineering teams will treat AI tools the way they treat CI/CD pipelines today: valuable, embedded, and mediated by human oversight. Teams will establish lightweight internal policies defining where AI can generate code, what requires manual review, and which tasks still require senior level decision-making. Companies will adopt practical guardrails because experience will show that AI without supervision is more expensive, not less.
Oscar Moncada, Co-founder and CEO, Stratus10
Connecting Good Ideas With Hard Data
By 2026, AI will connect good ideas with hard data directly. At Search Party, we had AI sort through thousands of creators and found partnerships we would have missed manually. The campaigns just felt more real. If you’re looking for new tools, find ones that don’t just automate but actually get what your brand is about.
Brandon Brown, CEO, Search Party
Microsoft Will Turn Windows Into the First Consumer & Enterprise Operating System With an Agentic AI Layer
In 2026, Microsoft will turn Windows into the first consumer and enterprise operating system with a true agentic AI layer. The early hooks are already visible in Windows today. Microsoft has been preparing the OS to host an ecosystem of autonomous helpers that perform tasks, shop for you, troubleshoot IT issues, and interact with applications without you driving every click. We already see previews of this direction in Windows Copilot. The next step will be a full agent marketplace where third party developers publish specialized agents that users or companies can install like apps. Once this launches, Windows will shift from a system you operate to a system that operates for you.
Jeremy Moskowitz, VP of Product Management for Endpoint Products, Netwrix
AI Will Turn Into A Competent Teammate
By 2026 AI will stop feeling like a chat window and start feeling like a competent teammate that quietly runs parts of your business. The real shift will be from asking a bot for answers to describing the outcome once and letting an AI agent keep working in the background across tools like email, CRM and finance. The companies that win will not just use the most advanced models, they will be the ones that wire AI into very specific workflows with clear guardrails, so it can take real action and still be trusted.
Vitaly Goncharenko, Founder, HoverBot
Using AI To Build Site Authority
I build AI tools for SEO, and I can tell you, the strategy is shifting. Big companies are done just chasing backlinks. They’re using AI to build actual authority, and AI is getting much better at finding credible sources and connecting with journalists. Our Backlinker AI clients get better results by letting the algorithm suggest which stories to go after, instead of just guessing. Honestly, it’s time to start using AI for your outreach or you’re going to get left behind.
Bennett Heyn, Founder, Backlinker AI
Increased Trust In AI That Shows Its Work
What’s changing fast is trust. Not trust in AI hype, trust in output. If AI can’t explain why it did something, people won’t rely on it. In 2026, AI that shows its work will win. Transcripts tied to sentiment. Routing tied to context. Recommendations tied to outcomes. We’ve watched ops teams go from excitement to skepticism in weeks when answers don’t line up with reality. Explainability stops that drop-off. It keeps humans in the loop without slowing them down.
Yaniv Masjedi, Chief Marketing Officer, Nextiva
The Era of Burning Money is Coming to an End
The AI hype is dying down with giants such as OpenAI losing massive amounts of money with each passing day. Across industries, business owners are seeing that AI features are not actually adding more value to the product. Instead, it seems like a race over who adds more AI tools without clear benefits for the end-users. Instead, it’s just impressing investors and scaring the competition. Seems like that era of burning money is coming to an end.
Daniel Kroytor, CEO, TailoredPay
AI’s Infinite Memory Will Redefine Cybersecurity
In the coming years, one of the biggest concerns for businesses will be what happens to their data inside AI. GenAI models operate in public cloud environments with virtually infinite memory and computational power – they can process anything and remember everything, unlike humans who have finite capacity and natural forgetfulness.
As AI becomes more deeply integrated into business systems, cybersecurity will need to evolve beyond traditional boundaries. In addition to protecting data through secure application delivery models, organizations will need clear policies and guardrails around how data is used, prompted, and shared.
We can’t assume these systems will forget – so businesses must be intentional about what data goes into models, how it’s managed within applications, and how to prevent it from making its way out into the world.
Cybersecurity will be no longer just about securing perimeters or endpoints – it’ll be about much more than that.
Prashant Ketkar, CTO at Parallels
Generative AI Value Unlocked
In 2026, the companies that will truly unlock the value of generative AI won’t be the ones chasing the latest tools. They will be the ones treating AI as a people-powered transformation engine. The organizations that don’t focus on the technology but instead focus on preparing their people for AI, fostering an AI-ready mindset, and embedding AI into the rhythms of daily work and culture will be the ones that see meaningful returns on their AI investment.
But this shift requires more than prompt trainings; it demands cultural adoption where wins are celebrated, communities of AI champions are cultivated, and where employees feel empowered to experiment, share successes, and build confidence together across the organization. Because that’s when AI becomes a catalyst for company-wide transformation.
Kristin Ginn, Founder, trnsfrmAItn
AI Agents Will Automate B2B Sales Pipeline
In 2026, AI agents will automate the entire B2B sales pipeline by orchestrating sequences in real time based on behavior and intent signals. They will replace manual handoffs between SDRs, AEs, and marketing with a process that adapts to buyer actions as they happen.
Joby Antony, AVP – Digital Marketing, Fingent
A Collaborator That Orchestrates Workflows Autonomously
By 2026, AI will shift from being a tool you use to a collaborator that orchestrates entire workflows autonomously. The real breakthrough won’t be bigger models—it will be agentic systems that can reason, verify, and act across applications with minimal human supervision. Companies will stop asking, ‘How do we integrate AI?’ and start asking, ‘Which processes can we hand off entirely?’
We’re Walking Into A Synthetic Horizon
Given the way things are heading, when we get to 2026, it will be like we’re walking into a synthetic horizon. The problem won’t be finding good information anymore, instead it will be figuring out what’s actually real. And the split between people is going to look different too. Some folks will be the ones steering the AI agents, and others will feel like the agents are steering them. A few people will have the money or freedom to unplug whenever they want, while everyone else stays stuck in a loop driven by agents. I believe the people who do well are the ones who can navigate through all that tech and still amplify real, human stuff the machines can’t copy.
Matthew Mead, Chief Technology Officer, SPR
Individualized On-The-Spot AI-Generated Visual Content
I’m betting that by 2026, AI will be generating visual content on the spot for each individual user. We saw this happen at Fotoria. Once we started creating real-time images for client brands, people started interacting more right away. The content just felt more personal. If you’re in branding or design, trying AI tools that customize visuals on the fly could give you a real edge.
Edward Cirstea, Founder, Fotoria
AI Automation Will Be Invisible
By 2026, AI automation will be invisible, just built into the tools we use daily. Voice assistants and predictive outreach will handle the repetitive stuff quietly in the background. At Simple Is Good Inc, we’ve seen manual errors and missed follow-ups drop for our clients since adding AI. It works best when you stop thinking of it as a separate tool and just make it part of the workflow.
Ralph Pieczonka, Director, Simple Is Good Inc
AI Adoption Will Accelerate Faster Than Regulation
In 2026, the world will continue to see AI adoption accelerate faster than regulation, forcing specific industries to reinvent processes and workforce models to stay competitive. As global capabilities diverge and the technology gap grows amongst nations, sovereign AI will be the defining tool for any country that wants to secure its autonomy and economic growth.
James Kaplan, CEO & Co-Founder, MeetKai
Employee Learning
By 2026, learning teams will finally step into the strategic influence they’ve long been positioned for. With most programs now operating at an ‘intermediate’ level, the next frontier is clear: moving from delivering training to driving measurable business outcomes. As organizations demand clearer links between learning, performance, and retention, L&D will become a critical voice in shaping company-wide strategy.
Brendan Noud, CEO and Co-Founder, LearnUpon
AI and MCP Vulnerabilities Shift from Warnings to Actual Security Events
Throughout 2024 and 2025, researchers uncovered weaknesses in AI frameworks and Model Context Protocols. Many teams rushed to connect large language models to internal workflows without clear safeguards, while attackers quietly studied the gaps.
In 2026, AI and MCP related breaches are expected to surface. Early examples will likely look similar to the mistakes organizations made during the first cloud migration wave: enthusiasm outpacing engineering discipline. Misconfigurations, over-permissioned connectors, and improvised integrations will create opportunities for compromise.
This change signals a maturing phase for enterprise AI. It is no longer enough to experiment. Companies will need structured approaches for validation, access control, and monitoring.
Marcel Calef, Americas Field CTO, ControlUp
Revenge of the Semantic Layer
Enterprise knowledge management systems will be restructured in 2026 with AI agents in mind. In order to complete complex tasks based on accurate information retrieval, agents will need new interfaces and permission structures to understand organizations’ vast repositories of data and experience.
Eva Nahari, Chief Product Officer, Vectara
From Software to Machines
In 2026, the conversation around AI shifts from software to machines that do real physical work. The last few years proved that knowledge work can be automated – now the pressure is coming from industries where the work is still overwhelmingly manual. In construction, for example, there are over 500,000 unfilled jobs and contractors routinely turn down projects because they can’t find skilled tradespeople.
What we’re seeing is a move away from ‘general-purpose’ robots and toward practical, task-specific machines that deliver immediate value. In our case, contractors aren’t asking about algorithms – they just want a robot that reliably lays tile so they can take on more work. This kind of physical automation is where 2026 is heading: not science fiction, just solving shortages that are already hurting businesses today.
Uncontrolled Data Growth Creates A Perfect Storm For Dramatic Change
Teams Will Need to Invest In People to Support AI
2026 will highlight something many leaders overlooked. Technology will keep moving fast, yet the real advantage will come from people who think clearly, learn quickly, and make good decisions under pressure. Education will feel this first. Young people already use AI as naturally as they once used search engines. Schools and universities will need to focus on critical thinking, communication, and good judgement because these shape how students use technology, not the other way round.
The same shift will reach workplaces. Teams that develop stronger human skills will adapt to new tools with confidence. Teams that do not invest in people will struggle, even with the best technology. AI will keep improving, but capability will decide the gap between those who keep up and those who fall behind.
An AI Energy Wall Will Spur A Race For Efficiency
The Definition of a Business Application Will Be Redefined
The Death of AI: Intelligence becomes Infrastructure
By 2026, we’ll see the “death of AI” as the headline we know it to be today. This, however,won’t mark the end of AI innovation, it will signal its maturity. Artificial intelligence will stop being the frontpage soundbite and start being the hidden layer powering everything from customer interactions to backend operations. Just as the internet quietly transformed from a futuristic idea into the backbone of modern life, AI will fade into the fabric of how work gets done. The focus will shift away from algorithms and model counts toward tangible business outcomes: faster problem resolution, sharper insights, and smoother customer journeys.
In this next phase, AI will be less about disruption and more about integration. Companies that once promoted “AI-powered” products will instead highlight measurable value: time saved, risks reduced, opportunities discovered. For leaders, this means rethinking how success is framed. It won’t be about adopting AI for AI’s sake, but be around embedding intelligence that enhances creativity, productivity, and decision-making. The “death of AI,” in truth, is the birth of something better: a world where technology disappears into the workflow, and only results remain visible.
The Beginnings of Real AI Investment in Factories Across America
To date, most US manufacturers have focused on retrofitting smart infrastructure into existing factories their plants. Which means in many cases, countries without legacy factory infrastructure have leapfrogged more traditional manufacturing powerhouses in smart factory design.
This makes 2026 the year US companies get serious about their future factory investments. We’ll see more U.S. manufacturers move from proof-of-concept automation to enterprise-level AI integration– tying robotics, data, and AI systems into a single operational loop.
Craig Melrose, Global Managing Partner of Mobility and Advanced Technologies, HTEC
The Days of Mouse and Keyboard Are Over
Within the next few years, human-computer interaction will shift from traditional interfaces to fully agent-driven systems, where AI agents communicate directly with each other to fulfill user requests. Websites, apps, and dashboards that we have all used and depended on for years will become secondary, as users rely on trusted agents to aggregate, interpret, and act on data automatically. Those agents are the new data brokers, automating the data discovery and data interpretation processes. Organizations that provide high-quality, auditable data which is a verifiable source of truth will dominate this new agent-to-agent ecosystem. Over time, transactional tasks, data analysis, and even decision-making will be handled seamlessly by AI agents, transforming workflows and user expectations.Quietly we will start building out “world models” where agents can understand, respond to text, voice, and images in interactive virtual 3D environments. The days of humans using a mouse and a keyboard will be over.
Chas Clawson, Field CTO, Security, Sumo Logic
Critical Thinking, not AI, Becomes a Differentiator
Human skills like critical thinking and ethical decision-making will become more valuable than ever as AI takes over routine tasks. It’s critical that organizations invest in these nontechnical competencies to ensure employees can interpret AI outputs, question assumptions, and apply judgement. The future of work won’t just be about mastering tools, it’ll be about pairing machine efficiency with human insight and expertise.
Erin Gajdalo, CEO, Pluralsight
AI Will Reduce the Limitations of Cybersecurity’s Reliance on Customer Data
Agentic AI Ends the Era of Standalone Software
Next year will mark the tipping point for connected intelligence. Software platforms that extend data and workflows across the enterprise will dominate, while isolated tools will fade into irrelevance. Agentic AI is already proving that productivity breakthroughs come from collaboration, between systems as much as people.
The next generation of AI agents won’t live inside individual apps. They’ll communicate, coordinate, and act across entire tech ecosystems, turning fragmented processes into fluid, intelligent networks. In this new era, standalone software simply won’t be able to compete. The demise of remaining on-premise software will accelerate, leaving just 15% of those companies over the next three years.
Ross Meyercord, CEO, Propel Software
AI Adoption Will Impact Leave Rates
As AI displaces entry-level workers, workforces will skew dramatically older, and older employees typically need to take leaves (e.g., parental or caregiving leave) at much higher rates.
Companies celebrating AI-driven efficiency gains haven’t done the math on what happens when their workforce demographics shift and leave utilization suddenly spikes.
The double impact of losing junior talent to automation while senior employees face increasing caregiving responsibilities will catch most HR teams completely off guard.
Samarth Keshava, CTO and Co-Founder, Sparrow
The ‘Rogue Agent’ Crisis: Verifying the Human Behind the AI
As the “personal AI agents” that moved from theory to product in 2025 become commonplace in 2026, the threat will no longer be simply spotting a deepfake. The new arms race will be in distinguishing a legitimate, authorized agent from a malicious one. This will force a radical evolution of liveness detection, shifting from “Is this a real human?” to “Is this agent under the control of the right, genuine human right now?
Andrew Bud, CEO and Founder, iProov
AI Agent Adoption Will Change The Nature Of Work
The nature of work will change completely in 2026 as companies increase their adoption of AI Agents. This transformation will begin in go-to-market and service teams, where customer engagement, support, and delivery are critical, before expanding across all business domains. Instead of managing tasks, companies will increasingly rely on agents to autonomously execute them, handling everything from routine processes to complex workflows. This evolution will fundamentally change how companies are built and scaled. Future organizations will be far leaner, basing their growth and expertise on a digital workforce of agents rather than traditional headcount. For enterprises, this shift will introduce new roles dedicated to building, training, and orchestrating these agents, reshaping internal structures and redefining growth dynamics, especially in customer-facing and service-oriented functions such as content and design.
Next year, the barrier to building agents will collapse, enabling small teams to achieve enterprise-level capabilities. At the same time, “vibe coding” will become a core part of the business stack. As LLMs continue to evolve, people will be able to deeply integrate hyper-tailored solutions on top of their current tech stack into their day-to-day operations, making AI a true execution layer of business. As a result, SMBs and startups will be able to compete at an infinite scale, unbound by headcount or hierarchy. Software will stop being a tool and start being a real collaborator – a teammate that contributes, executes, and evolves alongside humans.
Daniel Lereya, Chief Product and Technology Officer, monday.com
