Business Automation Trends That Will Define 2026

Nowadays, the automation sector is accelerating at a pace that's catching even forward-thinking companies off guard. Its growth signals a fundamental shift in how businesses approach efficiency, scalability, and competitive advantage. Recent research shows that 90% of organizations report increased demand for automation across departments over the past three years.

Companies that invested early in automation are now building on proven workflows and measurable ROI, while late adopters face a widening gap that compounds every quarter. But what’s important to highlight is that not all automation delivers equal value. The organizations seeing the biggest returns aren't necessarily throwing the most resources at the problem or deploying the flashiest AI tools. They're making strategic choices about which processes to automate, when to implement them, and how to measure impact beyond simple time savings.

At Rebbix, we've spent the past year working directly with businesses implementing automation across sales, operations, customer service, and other functions. We've seen which approaches consistently deliver results and which ones fall short despite promising early gains. Certain automation trends are fundamentally transforming business processes, while others remain more hype than substance.

In this article, we'll break down the automation trends genuinely changing how companies operate right now and give examples of their real-world applications. Let’s see what leaders of various industries are betting on.

#1 Agentic automation & multi-agent systems

If there's one automation trend that defines 2026, it's the shift from task-level automation to goal-driven systems that can plan, execute, and adapt across entire workflows. Agentic automation represents the evolution from tools that wait for commands to systems that understand objectives and determine the best path forward. 

UiPath research reveals that 78% of business leaders believe their organizations must fundamentally restructure operations to fully leverage agentic automation capabilities. This urgency is driven by the rapid pace of adoption: Gartner forecasts that 40% of enterprise applications will incorporate task-specific AI agents in 2026, which is a dramatic jump from less than 5% in 2025.

What makes agentic automation different from traditional automation is autonomy paired with reasoning. Instead of executing a single predefined task, these systems break down complex objectives into steps, make decisions based on context, and adjust their approach when circumstances change. Multi-agent systems take this further by deploying specialized agents that collaborate to solve problems too complex for any single system. For example, one agent might handle data validation while another manages fraud detection and a third coordinates customer communications — all working together toward a shared outcome.

Real-world implementations of agentic and multi-agentic automation:

• A leader in high-speed connectivity, Ciena, implemented an agentic AI assistant to handle internal IT and HR requests, automating more than 100 workflows such as access requests and approvals. This cut approval times from days to minutes and freed HR and IT teams from repetitive tickets so they could focus on higher‑value work.
• Bank of America deployed Erica, an AI-powered virtual assistant that uses agentic automation to improve customer service and reduce support costs. Erica provides personalized financial guidance and automates routine banking tasks through both voice and text-based conversations. The implementation resulted in improved customer engagement, with the article noting a 25% increase in customer engagement through AI-crafted personalized messages. Erica operates as a multimodal agent capable of assisting customers across multiple channels while handling complex financial inquiries autonomously.
• A Boston-based integrated health system, Mass General Brigham, implemented an agentic system for clinical documentation that automates note-taking and electronic health record updates. As a result, physicians reclaimed hours previously lost to administrative work, reducing burnout while improving care delivery outcomes.

#2 Hyperautomation

While agentic AI handles individual tasks autonomously, hyperautomation takes automation to the next level by orchestrating entire business processes from start to finish. This approach combines robotic process automation (RPA), artificial intelligence, machine learning, and process mining to create seamless, intelligent workflows that span multiple systems and departments. The market has caught on fast. Gartner reports that 90% of large enterprises listed hyperautomation as a strategic priority as of 2024, with companies racing to automate 30% of their processes by the end of 2026.

The results speak for themselves. Organizations implementing hyperautomation see immediate labor cost reductions of 40% as bots take over repetitive work, with some companies achieving ROI as high as 2,560%. But it's not just about cutting costs. Processing times drop by over 80% for tasks like expense processing and invoice management. Manual errors practically disappear. And employees finally get to focus on work that actually requires human creativity and judgment instead of endless data entry and form-filling.

What makes hyperautomation different from traditional automation is its ability to handle complex, exception-heavy processes that previously required human judgment. By combining multiple technologies — computer vision, natural language processing, predictive analytics, and workflow orchestration — hyperautomation systems can adapt to changing conditions, make intelligent decisions, and continuously optimize themselves. That's why it's gaining traction in heavily regulated industries like financial services and healthcare, where you need both speed and bulletproof accuracy.

Hyperautomation in practice:

• Unilever deployed a comprehensive hyperautomation platform across 124 factories worldwide, integrating real-time data, automated systems, and digital twins to optimize production. The results include a 3% increase in Overall Equipment Effectiveness (OEE), 5% higher labor productivity, and an 8% reduction in costs across the entire manufacturing network.
• Nike collaborated with Cognizant to bring hyperautomation into its technology operations, combining RPA, AI, and ML across customer personalization, data-driven supply chain optimization, and integrated operational tools, showcasing how advanced technologies can collectively drive end-to-end automation and productivity gains. The hyperautomation approach enables Nike to predict product demand with greater accuracy, forward-position popular products to reduce lead times, and deliver 24/7 customer service capabilities. 
• An American retail automotive services company, Valvoline, deployed hyperautomation to transform their Security Operations Center after their team was cut from 24 to 12 members, replacing a code-heavy legacy SOAR system that created operational bottlenecks. The no-code platform automated phishing detection, alert handling, and incident response across Microsoft 365, Defender, and CrowdStrike, saving 6-7 analyst hours a day and achieving operational ROI within 48 hours of deployment.

#3 Automation-as-a-Service (AaaS)

The problem with traditional automation is that you need to buy servers, hire specialists, spend months on implementation, and hope your investment doesn't become obsolete before you see returns. Automation-as-a-Service (AaaS) throws that playbook out the window. Instead of building automation infrastructure from scratch, companies simply subscribe to cloud-based platforms that deliver RPA, AI, and workflow automation capabilities on demand. Pay monthly, scale as needed, and let someone else worry about updates and security.

The shift to AaaS is also about speed. Traditional automation projects could take 6-12 months before delivering value. With AaaS platforms, businesses are automating processes within weeks and seeing ROI within six months. Need to scale up for peak season? Add more bots. Demand drops? Scale back without being stuck with unused capacity. This flexibility is driving rapid adoption. 71% of enterprises have already automated at least one major business function using cloud platforms, particularly in finance and HR, where repetitive tasks are abundant.

What's really accelerating AaaS adoption is how accessible it's become. Availability of low-code and no-code platforms means that business analysts and department managers can build automations without writing code. This "citizen developer" movement is transforming how companies approach automation. Instead of waiting months for IT to build something, teams can prototype and deploy solutions themselves. The platforms handle the complexity behind the scenes: integration with existing systems, security, compliance, and continuous updates with the latest AI capabilities.

Cases of companies benefiting from Automation-as-a-Service:

• A major Coca-Cola bottler, Coca-Cola İçecek, operates across 12 countries with over 10,000 employees and was drowning in logistics paperwork. They implemented UiPath automation that tackles shipment document reconciliation, saving 12,000+ hours annually and eliminating 300,000 printed pages in the process. Beyond the obvious efficiency gains, they improved payment terms by 20% and sped up credit approvals by 5% just by removing bottlenecks where documents sat waiting for unnecessary sign-offs.
• Osaic, a leading financial services firm, implemented Automation Anywhere's cloud-based AaaS platform to streamline its back-office operations and client service processes. The company achieved an impressive 186% return on investment in just the first year of deployment, demonstrating how quickly cloud-based automation can deliver measurable value without the lengthy implementation cycles of traditional on-premise systems.

#4 AI-powered intelligent automation

Traditional automation follows rules. AI-powered intelligent automation breaks them — or rather, writes new ones on the fly. By combining robotic process automation with artificial intelligence, machine learning, and natural language processing, intelligent automation can handle unstructured data, make judgment calls, and actually learn from experience. It's the difference between a bot that can file invoices and one that can read handwritten notes, understand context, flag anomalies, and route exceptions appropriately.

What's driving the rush? For example, financial organizations implementing intelligent automation report 30-300% ROI within the first year. Companies are seeing processing time reductions of 75%, accuracy rates exceeding 95%, and cost savings amounting to millions of dollars annually, depending on organization size.

Here's what makes intelligent automation different: it doesn't need perfect data or rigid processes. Computer vision can extract information from messy documents. Natural language processing understands customer intent across channels. Machine learning spots patterns humans miss in milliseconds with 95% accuracy. And unlike rule-based bots that break when anything unexpected happens, intelligent systems adapt. They get better over time, continuously learning from new data and edge cases.

Examples of AI-driven intelligent automation in action:

• Siemens implemented intelligent automation for predictive maintenance across industrial assets, including turbines, using AI and machine learning to analyze sensor data and predict equipment failures before they occur. The system reported reduction in downtime and significantly enhanced energy production efficiency by enabling proactive maintenance scheduling instead of reactive repairs.
• Financial technology company Klarna deployed "Kiki," an internal AI assistant that handles over 2,000 employee knowledge queries daily across the organization. With 87% of staff using generative AI regularly for information retrieval and workflow automation, Klarna estimates the system saves approximately $40 million annually in support costs while dramatically reducing the time employees spend searching for information or waiting for responses from help desk teams.
• At Rebbix, we developed an automated project estimation system that delivers accurate preliminary estimates in 90 seconds through 5-7 simple questions. It replaced the traditional 2-day process requiring multiple discovery calls and back-and-forth correspondence. This AI-based automated workflow incorporates domain research capabilities to analyze existing platforms, validates timelines against real project portfolios, and generates comprehensive outputs including technical architecture, technology recommendations, team composition, and milestone breakdowns. 

#5 B2B buying process automation

The way businesses buy from each other is getting a serious upgrade. By 2028, 90% of B2B buying decisions will be AI agent-intermediated, pushing over $15 trillion in B2B spend through automated channels. What used to require weeks of back-and-forth emails, multiple discovery calls, and endless manual paperwork now happens through self-service portals, AI-powered procurement platforms, and automated workflows that guide buyers from initial research to final purchase.

Modern B2B buyers expect the same seamless experience they get with consumer shopping. They want transparent pricing, real-time inventory visibility, instant quotes, and the ability to complete entire transactions without talking to a sales rep. For example, 75% of B2B buyers prefer a sales experience without representatives, and over 50% of purchases are now completed through digital self-service channels.

The ROI on buying process automation is hard to ignore. Companies implementing AI-driven procurement solutions are seeing their sales cycles cut by more than half, while simultaneously generating more leads and reducing costs. Organizations that take it a step further by aligning their sales, marketing, and customer success teams through RevOps are significantly more likely to exceed revenue targets while keeping operational costs in check.

Cases showing tangible results of buying process automation:

• Australian dental and medical supplies distributor AHP Dental & Medical replaced their phone and email-based ordering system with an integrated BigCommerce B2B platform connected to their ERP. Online transactions jumped from 25% to 75% of total sales, while automated workflows eliminated an estimated 11,000 hours of manual data entry annually (equivalent to six full-time employees).
• Furniture manufacturer Steelcase deployed thousands of customer-specific microsites across their dealer network, each with unique branding, product catalogs, and purchasing rules. For major clients, they implemented seamless punch-out catalog integration, enabling customers to browse the Steelcase web store from within their internal e-procurement systems and automatically transfer shopping cart contents back for internal approval and purchase order generation.
• Equipment rental company Sunbelt Rentals integrated Adobe Commerce with Adobe Marketo Engage, transforming their e-commerce site into a proactive marketing channel. Their automated Abandoned Cart Nurture campaign sends personalized follow-up emails with location-specific inventory information to customers who add items but don't complete reservations, turning what would be lost sales into recovered revenue through targeted re-engagement.

Conclusions

The automation trends we’ve explored are already reshaping how businesses operate — and their impact will only grow. From agentic systems that autonomously manage complex workflows to intelligent automation that learns and adapts, companies across industries are proving that strategic automation delivers measurable results: shorter cycle times, lower operational costs, and teams freed from repetitive work to focus on innovation and growth.

What separates successful implementations from disappointing ones isn't budget size or technical sophistication. It's strategic thinking. The organizations seeing the strongest returns start with clear objectives, choose processes where automation delivers maximum impact, and measure outcomes beyond simple time savings. They understand that automation isn't about replacing human judgment but about augmenting it, handling the predictable and repetitive so people can focus on work that requires creativity, empathy, and strategic thinking.

The question isn't whether to automate, but where to start and how to do it right. If you're ready to transform your business operations with smart automation, our team is here to help. Let’s talk and identify high-impact automation opportunities for your company to build solutions that deliver results.

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