Future of the enterprise: The digital workplace trends that will redefine how we work in 2026

Highlights 

• Manual work is slowing down operations, creating unnecessary work for HR/IT and compromising ROI and competitiveness. Agentic AI is designed to address all of the above by helping automate workflows and making employee self-service a reality wherever possible.                  
• Employee experience is now a measurable performance driver — and organizations are redesigning digital environments to reduce friction, personalize support, and simplify work.
• Autonomous, agentic AI is becoming foundational to enterprise operations in leading enterprises, helping to shift the digital workplace from reactive support to proactive, end-to-end workflow execution. 
• Rapid AI advancement is accelerating the need for continuous reskilling and upskilling, requiring organizations to strengthen workforce readiness and AI literacy.
• The talent market remains volatile, and employers must evolve hiring processes, role definitions, and candidate experiences to stay competitive.
• Leaders are consolidating tech stacks, embracing productivity intelligence, and unifying support to create a more streamlined, integrated, and AI-ready digital workplace for 2026.

The year 2026 is shaping up to be a turning point for how work gets done, with AI moving from pilot projects to everyday operations and hybrid work becoming the norm. 

But as a lot of enterprises are finding, that means employees also expect workplace technology to actually work.

For enterprise HR and IT leaders, that often ends up looking like constant support requests and a growing mix of tools that don’t talk to each other — on top of wrestling workflows built for a very different way of working. 

As AI spending increases, you’re now under pressure to modernize systems and improve employee experience, while showing clear business impact. But without consolidation, it’s nearly impossible to scale adoption, maintain governance, or show measurable ROI.

Fortunately, there are some new trends reshaping the enterprise in 2026, aimed at resolving these inefficiencies and creating a more connected, cohesive business environment. Here’s how your org can turn these trends into a competitive advantage.

For a deeper dive into the IT trends shaping the future of work, see our companion guide: 2026’s AI Trends in IT: The Year AI Matures.

Trend 1: Autonomous AI becomes the operating system of work 

AI is quickly becoming the operating system of work itself, not another tool in your stack. Rather than supporting employees from the sidelines, some agentic AI tools can assist in executing tasks across systems and support decision-making, helping to move work forward more efficiently. 

This shift exposes the limits of legacy support models. Ticket queues, manual triage, and slow resolution cycles don’t scale in an environment where there’s constant demand and growing complexity, and they drive up costs as a result. 

This new model (which McKinsey terms “enterprise-scale multiagent orchestration”) involves multiple AI agents coordinating to handle work that once needed entire teams. 

Employee expectations have also changed, and that’s another big reason why agentic AI is gaining traction now. They want immediate answers and instant outcomes, not forms and handoffs or waiting in line for help. Agentic AI has the potential to reason, plan, and complete multi-step workflows across systems without human intervention. 

This foundational shift sets the stage for nearly every other digital workplace trend we’ll cover below. 

The shift from answer engines to action engines 

Legacy AI tools like chatbots are mere answer engines. In essence, they are smarter search bars that point employees to the right policy or how-to guide. Helpful, but it still leaves the actual work in human hands. 

Now, AI is moving toward action engines. Some agentic AI assistants can update systems, troubleshoot issues, and carry out tasks across tools without bouncing employees between platforms. 

In fact, a McKinsey study found that domain-specific agents deliver up to 35% higher measurable impact than generic assistants, largely due to being embedded into real workflows. 

Operationally, this changes everything. Rather than generating more tickets, agentic systems can assist in resolving them. Instead of routing requests, it can fulfill them. That leads to faster resolution times, fewer handoffs, and far less dependence on manual processes. 

Proactive support replaces reactive ticketing 

Rather than waiting for something to break and logging a ticket, some AI tools now monitor systems, usage patterns, and user behavior to spot issues before they escalate into real problems. That’s when:

• Downtime becomes easier to prevent.
• Delays can be caught earlier.
• Repeat requests start to disappear.
• Support teams spend less time putting out fires and more time improving the overall experience. 

Over time, this reduces operational drag and helps eliminate the burnout that comes from managing endless queues. 

In 2025, many leaders still thought of AI mainly as chatbots or analytics tools, but that has changed. Enterprises now see that agentic AI can be deployed to reason across systems, plan multi-step actions, and complete workflows on its own. 

Trend 2: Employee experience becomes a north star for productivity 

Employee experience can’t be a low-budget afterthought anymore. It’s become a core driver of productivity and retention. When repetitive tasks or slow responses bog down HR and IT teams, employees get frustrated and satisfaction drops, resulting in a measurable impact on the bottom line. 

Hybrid work and remote onboarding have made these gaps even more visible. Confusing systems, fragmented processes, and inconsistent support leave employees struggling to get what they need, when they need it. 

In 2026, orchestration is expected to complement automation as a key capability of IT.  Leading companies are redesigning the employee experience with this in mind, focusing on simplicity and immediacy, often with AI-driven personalization. 

The stakes are high: Better experiences retain talent and boost productivity while reducing costs — poor ones hurt employee satisfaction and overall performance.

Personalization at scale 

When a new team member can’t figure out how to submit a time-off request without jumping between multiple systems, that frustration might leave them second-guessing your organization. Role-aware, context-aware, and time-sensitive assistance helps employees get answers or info at the moment of need. 

As hybrid work grows more complex, generic responses just don’t cut it. Tailoring guidance and actions to each employee’s role keeps workflows moving and makes the digital workplace feel intuitive rather than confusing. 

Reducing cognitive load and complexity 

When an employee is trying to onboard remotely, they shouldn’t have to switch between email, an HR portal, and Microsoft Teams just to get one request completed. Constant notifications and disconnected systems make it hard to focus and end up slowing work down. 

Simplifying navigation and enabling conversational interactions eases that burden. Systems that are easier to use help employees move faster and make fewer mistakes along the way. 

Discover effective strategies to measure and improve employee experience across your workplace.

Trend 3: Employers are focusing on reskilling and upskilling to support AI ROI

AI is reshaping the skills employees need to succeed, and job responsibilities are evolving faster than traditional training can keep up. Today’s workers need a baseline fluency with AI tools, automation concepts, and digital workflows just to stay effective. 

This shift has also fueled the rise of citizen developers — employees using low-code or no-code tools to build their own AI agents. EY’s survey shows 84% of employees are teaching themselves about AI outside work, and 83% say their skills are self-taught. 

The most critical capabilities include:

• AI literacy: Knowing how autonomous systems think and act
• Data fluency: Making sense of insights from intelligent systems 
• Cross-functional problem-solving: Collaborating across IT, HR, Security, and Operations teams to redesign workflows with AI

To help employees develop these skills and keep pace, companies are building internal academies and using AI-powered learning tools to close skill gaps and reduce burnout. 

Learn how companies are reskilling employees to turn AI investments into measurable business impact. 

Trend 4: Talent market turbulence reshapes workforce strategies 

Talent markets are anything but stable right now. In fact, 69% of organizations are struggling to fill full-time roles due to talent shortages and recruitment challenges, including low applicant numbers and candidate ghosting. The ways people want to work have shifted too, making traditional hiring approaches feel slow and out of step. 

Candidates tend to expect a faster, more transparent hiring experience, with clear communication and responsive processes at every step. Roughly 72% say it should take three weeks or less. 

That expectation goes beyond simple convenience. It directly affects how applicants perceive your brand and whether they’ll accept an offer or walk away.

As roles blend and workforce strategies evolve, HR leaders are being asked to lead with agility and rethink talent pipelines, while making candidate experience a key part of their employer brand.

Roles evolve as AI augments work

Imagine an operations manager who used to spend hours reconciling data across multiple systems each week. When AI handles those repetitive tasks, they can focus on analyzing trends and recommending process improvements instead. 

Hybrid skill sets that combine business knowledge, technical know-how, and problem-solving are also in high demand. Employees who can navigate both operational and technological domains are essential for driving innovation and efficiency. 

HR faces rising pressure to deliver high-quality journeys 

HR teams are often expected to deliver faster, smoother experiences across the employee lifecycle. That means faster hiring cycles with clearer communication and workflows designed to minimize bias, all while keeping onboarding seamless for new employees. 

AI has the potential to help in practical ways. Teams are already using it to:

• Screen resumes for top candidates
• Route applications to the right hiring managers
• Schedule interviews automatically
• Track employee onboarding progress

Discover how AI is driving HR digital transformation, creating seamless experiences for employees. 

Trend 5: Agentic AI unlocks deep value across systems 

IT leaders are under pressure to show measurable outcomes from their AI investments. While traditional AI waits for prompts, agentic AI has the ability to act as an active participant — planning, using tools, and executing workflows. But an agent’s capabilities depend on access to the tech stack.

Many enterprises have overlapping tools and redundant workflows, resulting in complexity that slows productivity. Agentic AI plays a major role in changing that dynamic by integrating systems and creating compatibility, supporting better governance, performance, and employee experience. 

Instead of standalone AI tools, enterprises are moving to full agentic platforms that connect natively to HRIS, ITSM, IDP, IAM, ERP, and collaboration tools. 

Since agentic AI can be embedded in the data layer, it has the ability to actually get work done, not just talk about it. With a consolidated, integrated stack, it’s capable of executing multi-step reasoning, such as spotting a supply chain bottleneck, alerting a manager, and drafting a ticket for resolution — with minimal human intervention. 

Learn how agentic AI is powering digital transformation and streamlining enterprise operations, then explore some real-world examples.

Trend 6: Real-time visibility becomes the new productivity mandate 

If you’re studying last month’s productivity dashboard, you’re looking into a rearview mirror. Traditional dashboards are backward-looking and often disconnected from the actions teams need to take. 

Enterprises now need real-time visibility that reveals where employees struggle, where friction slows workflows, and where automation can make the biggest difference. This shift takes reporting from static snapshots to predictive intelligence that helps you plan resources and fix issues based on data-driven decisions. 

Real-time visibility into digital friction

Seeing where work slows down across systems and teams helps leaders identify bottlenecks, dropoffs, and recurring issues, like repeated ticket escalations and delayed approvals. 

With these insights, you can prioritize initiatives based on the number of employees affected, the impact on productivity, and the effort needed to fix them. You can also focus resources on the processes causing the most pain and avoid investing in projects that don’t improve employees’ day-to-day experience.

Predictive decision-making 

Predictive intelligence helps leaders anticipate issues before they disrupt work. Analyzing patterns in tickets, interactions, and system usage allows some AI tools to detect emerging hotspots — like surges in requests — potentially before they become major problems. 

In 2026, expect to see some of these models becoming domain-led and context-aware. Distributed intelligence, tailored to business units, provides timely insights that are actionable and tied directly to workflows. This lets you anticipate satisfaction dips or productivity bottlenecks and plan resources effectively. 

Learn how predictive intelligence can enhance employee experience and drive smarter operations. 

Trend 7: Unified employee support is emerging as a new standard 

Cross-department workflows often break because IT, HR, finance, and facilities rely on separate systems and support teams. Employees face delays and handoffs when tasks span multiple functions. 

That’s why many enterprises are shifting to AI-powered, unified help layers to route, resolve, and coordinate requests across departments, eventually eliminating the need for separate help desks. Employees get fast, consistent support through a single conversational interface that works across systems.

Consolidated support can reduce the number of tickets and cases filed and speed resolutions. It has the potential to simplify the employee experience and set a new standard for how work gets done. 

Discover how self-service employee support can streamline workflows and boost satisfaction. 

Trend 8: AI adoption becomes a top enterprise success metric 

In 2025, many organizations rushed to deploy AI, but few saw real business impact. In 2026, measuring success means focusing on adoption, not deployment. Without employee trust and clear workflows, even advanced AI tools struggle to deliver value. 

Enterprises that prioritize adoption, usability, and integration may begin to see AI drive productivity and measurable ROI across the business. 

Why adoption matters as much (or more) than deployment 

MIT reports that 95% of generative AI pilots fail, mostly because employees don’t adopt the tools — not because of flawed technology. Many organizations spend heavily on AI that teams don’t understand or trust, leaving potential value untapped. 

Real impact comes when AI is woven into everyday workflows, helping employees complete tasks faster and make informed decisions to drive measurable results. Adoption, not deployment, is what takes AI from a pilot project to a true business advantage. 

What successful adoption looks like 

Successful adoption starts with a consumer-grade experience that feels as intuitive as Gemini or ChatGPT, so employees actually use it. Clear governance and explainability play an outsized role in building trust and helping teams understand how AI contributes. 

The most effective AI assistants are embedded directly into workflows, guiding tasks and resolving issues within systems employees already use. 

How AI operationalizes trends across the enterprise 

Some AI tools can act as a connective layer across your business, enabling personalization, automation, predictive insights, and unified support by integrating tech stacks. 

Enterprises that adopt this type of platform-based approach may be best positioned to capitalize on these trends. Agentic AI requires an integrated environment to be able to operationalize workflows end-to-end and reduce friction across systems, functions, and processes.

When you view AI as foundational infrastructure embedded into operations, rather than bolted on, you can unlock the potential to transform work from a series of disconnected tasks to a seamless, efficient experience. 

How enterprise leaders can prepare for these trends

Business leaders can take strategic steps to harness AI’s potential to improve employee experience and build a more agile, productive workplace. 

Assess digital workplace maturity 

Evaluate your digital workplace maturity to identify gaps in employee experience, support processes, and system integration. Focus on high-impact workflows where improvements can be measured to help ensure that AI and process change investments deliver tangible results for your employees and the business overall. 

Prioritize AI-ready ecosystems 

Focus on platforms that integrate seamlessly with existing systems, and automate workflows from start to finish. Avoid point solutions that add complexity and maintenance overhead. A connected, scalable AI ecosystem better supports adoption and streamlined operations in service of  maximizing value across functions and teams. 

Build momentum through quick wins 

Start with automated workflows that tackle high-friction processes or reduce ticket volume. Early successes demonstrate value and build stakeholder confidence, creating momentum. 

These quick wins lay the foundation for broader transformation, helping to accelerate adoption and pave the way for more ambitious AI-driven improvements across the organization. 

Strengthen AI governance and real-time oversight 

Nearly half of all enterprise AI governance frameworks are expected to include real-time edge monitoring and adaptive compliance this year. Increasing regulatory and internal pressure means organizations may want to prioritize AI fairness, explainability, and accountability. 

Leaders need clear visibility into how AI agents work, not just periodic audits. Strengthening governance and centralizing oversight, while continuously tracking decisions, may help reduce legal, financial, and operational risk. 

Move toward a more intelligent enterprise 

The digital workplace is already reshaping itself, and organizations that act now are more likely to gain a competitive advantage. Moveworks helps enterprises modernize by supporting these growing trends around agentic AI adoption, workflow automation, and employee experience. 

As an all-in-one agentic AI platform, Moveworks is designed to help enterprises leverage agentic automation, conversational language understanding, and workflow orchestration. The goal is to streamline tasks and allow employees to work faster with less friction. 

Moveworks helps you embed agentic AI into everyday operations. It is designed to simplify  integrations, automate multi-step processes, and deliver consistent support across functions, for a smarter and more efficient enterprise. 

Explore the Moveworks platform to see how it can help your organization build a more efficient digital workplace.