We asked Tech Leaders for their 2026 predictions related to targeting topics like funding, AI, hiring, culture, return to the office vibes, and more! Here are their responses:
AI makes creativity more valuable—when humans provide the right context.
When marketers create content from the same models and use similar prompts, nothing stands out in a differentiated way. More AI use means that the murky middle of creative quality will expand, with only the outliers earning consumer awareness and consideration. However, AI still holds the keys to unlocking access to creativity at scale, if the machines have the right context on what your consumers care about. The brands that will win and gain a massive competitive edge will use AI to rapidly iterate, test, and elevate ideas that will break through, using real consumer feedback to ensure lasting brand equity.
The Rise of Human-and-Machine-Centered Data Ecosystems – “We’re moving toward a world where data platforms won’t primarily serve people anymore; they’ll serve machines. The new consumers of data are AI agents, which will increasingly drive decisions, generate insights, and automate processes at speeds humans can’t match. These AI agents will require direct, governed, real-time access to all enterprise data to reason, generate, and act effectively. As AI agents become the primary consumers, enterprises must decide whether their data governance models empower or constrain them. This shift fundamentally changes everything about how we build and operate data infrastructure, from architecture and pipelines to governance and security, demanding a new approach that prioritizes machine-first accessibility without sacrificing trust or compliance.”
Hybrid AI Becomes the New Default – “The ‘cloud-everything’ era is coming to an end. Data gravity, sovereignty laws, and inference cost control are drivers for on-premises and model-to-data architectures. Enterprises are realizing that critical AI workloads need to remain close to their data, whether on-premises or in hybrid environments, to meet stringent requirements for performance, compliance, and data sovereignty. As a result, DevOps and data teams will increasingly build intelligent, governed ‘AI factories’ inside the enterprise, integrating AI pipelines directly with existing systems rather than relying solely on public cloud services. This approach ensures organizations can scale AI responsibly while maintaining control over sensitive information and operational efficiency.”
Prediction 1: In 2026, the companies that succeed with AI won’t be the boldest; they’ll be the ones with real guardrails. The question will shift from “Can AI do this?” to “Should AI do this?”
2025 was the year of experimentation. Looking ahead to 2026, curiosity will give way to commitment as enterprises start to rely on AI agents as business-critical tools. But this psychological shift – moving from testing agents to trusting them – will widen between those who succeed and those who don’t because of one defining factor: security and governance. Companies that invest upfront in defining clear controls and guardrails will unlock the transformative productivity gains that have long been marketed. Those that rush to deploy without proper oversight, on the other hand, will face public failures that damage their brand and erode trust. Flashy demos may impress, but they rarely endure. The next phase of AI maturity depends on learning to delegate responsibility. Governance is not a box to check; it is the strategy. Those who understand this will turn AI from theater into lasting impact.
Prediction 2: CFOs will kill more AI projects than CTOs launch, as the era for AI for innovation’s sake ends and budget holders demand proof.
Enterprises are reaching the end of the “AI for AI’s sake” era, and this will crystallize next year when finance teams stop politely nodding at AI roadmaps and start demanding P&L impact in quarters, not years. The vendors who survive will be those who can answer one simple question: What specific salary expense does this replace, or revenue will this generate? A sharp divide will form between vendors offering quantifiable cost reduction and those offering aspirational transformation, and only one will survive procurement.
Prediction 3: The most valuable AI agents won’t be the ones that you ask questions to, but the ones that alert you to problems you didn’t know existed.
The next wave of AI innovation will be defined by agents that act before they’re asked, but the real differentiator will be how effectively humans stay in the loop. These systems won’t wait for prompts; they’ll monitor markets, compliance landscapes and customer signals in real time, surfacing insights and taking action autonomously. Yet human judgment remains critical, providing the context, ethics and nuance that AI cannot replicate. As organizations scale, they must design systems where oversight is built in, not bolted on, with clear frameworks defining when and how people step in and remain accountable for outcomes. The companies that get this balance right, where humans and machines operate in true tandem, will build the trust and integrity needed to stay ahead of the curve.
Workflow management, not creation, will become the new enterprise battleground.
Enterprises spent a decade making workflow creation simple, but as AI-driven steps multiply and constantly change, the hard work of keeping workflows reliable begins. AI models evolve, prompts drift and vendors quietly update APIs, leaving yesterday’s functioning processes suddenly unstable. Teams that assume their current automation patterns will survive today’s AI variability will spend 2026 untangling silent failures, broken handoffs and processes they no longer fully understand. The teams that will stay ahead will treat workflows like living software – observable, versioned, validated and rigorously managed.
The winning story of 2026 will be that customers pay for the strongest outcomes, not the fanciest models. With economic headwinds tightening margins, buyers will demand AI solutions that deliver measurable business impact: lower costs per task, faster execution, tangible revenue gains, high ROIs, etc. And with enterprise leaders now facing pressure to scale performance and increase productivity amid hiring freezes and fragmented tech stacks, AI agents are indispensable tools for doing more with less. Correspondingly, enterprise AI spending will shift from experimental innovation budgets to core spending, cementing AI as a fundamental driver of operational performance rather than a speculative investment.
Email wins the attention war
Consumers are spending less intentional time on social media and growing more skeptical of SMS promotions, with many increasingly viewing marketing texts as spam. Meanwhile, email remains one of the few digital spaces customers actively choose to engage with.
As brands face more noise across emerging channels, the inbox becomes the place where attention is earned—not borrowed.
While only 41% of small business owners expect email to be their most impactful channel in 2026—compared to 58% who cite social media ads and posts—our data consistently shows that email delivers the most reliable and sustained customer engagement. The difference-maker is execution.
Customers are savvy, and the businesses that earn opens and clicks will be those that use personalization and automation to deliver the right message at the right moment.
The bloom is off the AI rose in terms of jobs it promised to eliminate. In 2026, I expect to see many leaders hiring back the talent they felt AI could remove the need for. Provided the economy remains somewhat stable, we should see a return to hiring for all types of roles – even those that took hard hits: Marketing, Business Development, and Software Development. But there will be less roles and hiring will be more discerning. Entry-level roles will still be hard to come by, and those able to land them will stand out through leaning into learning & using AI tools to deliver efficiencies to repetitive junior tasks.
The SOC Career Path Disruption:
As more major enterprises deploy agentic AI, the entry-level SOC alert triage will fade away. Tier 1 and tier 2 analysts will use AI tools to accelerate investigations and gain real-world, hands-on experience. This will compress traditional career paths, enabling analysts to advance into senior, more strategic roles faster than before. The SOC will transform from a center of basic alert handling to a hub of high-impact security expertise.
2026 Will be the Year the Investment in AI Pays Off:
More organizations will see their investments pay off as AI moves from infrastructure build-out to outcome-driven applications. While leading adopters have already achieved returns, the broader market has struggled to achieve meaningful payoff in day-to-day productivity. That gap has fueled fears of a so-called ‘AI Bubble,’ where all this spending might seem poised to collapse under its own hype. Companies that have laid the groundwork will start shipping agentic applications that materially change how work gets done, delivering measurable, end-to-end productivity gains rather than incremental efficiency wins.
The Year of ‘Agent Washing’:
When agentic applications begin to see meaningful results, everyone will want a piece of the pie. This will lead to a phenomenon of ‘Agent Washing’ where we will have to distinguish between organizations that simply want to claim they have an AI agent versus the AI agent that drives meaningful outcomes.
Not all organizations have the resources or power to commit to making an AI agent that is actually effective. We will see cases of AI agents that fail for a wide array of reasons, ranging from faulty technology, agents that are prematurely brought to market and even agents that were never going to work in the first place. Many teams will walk away saying “agents aren’t ready,” when the real problem was under-scoped use cases, hobby‑level investment and no clear success criteria. The signal security leaders will look for is not “Do you have an agent?” but “Can it reliably deliver the defensive outcomes you claim?”
The bachelor’s degree will stop being the only entry point to career advancement.
The “earn a degree once and you’re set” model is dead. Short-term credential enrollment grew 6.6% in fall 2025, the biggest increase across all program types. Certificate enrollment is up 28.5% since 2019. Learners want efficient, direct pathways to employment—and many are finding them without traditional degrees or using microcredentials to pivot into new fields.
This shift is being driven by both workers and employers. 93% of organizations cite retention as a top concern, with career development through learning as their primary strategy to address it. Workers are responding: 57% are currently upskilling, driven by economic pressure and rapid technological change. They aren’t going back for second bachelor’s degrees—they’re stacking credentials that address immediate skill gaps..
In 2026, universities will compete by truly understanding their learners—and designing for both experience and outcomes in a changing economy.
Many students now judge their university the same way they judge Amazon or Apple. In fact, 78% compare their university’s service to the service they receive everywhere else. That expectation is about to transform higher education.
Amazon and Apple aren’t successful solely because of their products—they succeed because they obsess over the consumer. They anticipate needs, remove friction, and design for outcomes. In 2026, universities will need to bring that same discipline to how they serve students.
This doesn’t change the mission-driven core of great universities — student-centricity and academic purpose aren’t in conflict. It means personalizing learning pathways with adaptive curriculum and flexible pacing. It means transparency, responsiveness, and continuous support—not treating tuition as a one-time transaction. And it means designing programs with the rigor consumer brands apply to product development: understanding what students need, measuring whether those needs are being met, and improving constantly.
More universities will start asking the same questions top consumer brands ask every day:
What do students want? Are we meeting their needs? How do we improve? The institutions willing to answer those questions honestly—and act on the answers—will be the ones that thrive.
Assessing employee satisfaction is shifting. It’s got to be more about hearing the employee voice on outcome based questions such as:
“Do you feel a sense of belonging?”
“Do you feel you are growing in your role?”
“Are you achieving goals you set out for yourself?”
And then narrowing the gap with what employees are saying and actions that are being taken. Employees, like most people, want to be heard, and showing action is the best way to do this.
Voice AI is going mainstream!
As valuations have come done (for most), private equity activity will continue to accelerate and we’ll see a lot more M&A. There will be a huge opportunity to combine AI/Agentic nascent players with traditional SaaS that has already solved the distribution problem.
By 2026, ‘return-to-office’ debate will finally die. The pre-pandemic workplace was no panacea and this year we’ll finally admit the way we work has fundamentally changed. Savvy leaders will wake up and realize their teams are starved for true meaning and real human connection, and seek novel ways to revamp their company cultures. This will become a powerful differentiator in attracting and developing top-tier talent.
I’m typically an optimist when we head into a new year. It’s just how I’m wired. However, I’ll admit my optimism has been chipped away over the last few years by tough economic conditions and the continuous cycle of layoffs.
Last year, for example, felt like an “AI pause.” It was a period of limbo where companies and individuals were unsure how AI would truly affect them… from internal use to customer facing solutions, to the fear that AI might replace us all.
By the end of last year, it felt like everyone found their groove. We realized that AI isn’t replacing jobs, at least not for now, but instead it’s giving everyone “superpowers.” We’re seeing a shift where AI is used to make us more productive, efficient, and creative.
Heading into this year, my optimism is back – largely due to the positive energy I saw in Q4. We saw massive funding rounds for high profile AI companies like 7AI and Suno, proving that “Agentic AI” is more than just hype. Plus, for the first time in a while, we’re seeing companies back in growth mode and hiring again.
I think 2026 will finally be a year of “normal” activity and steady growth. It might not be rocketship growth, but it’s positive and sustainable—and I’ll take that any day!