2025 will be the year of AI maturity in the enterprise. The evolution of AI has reached a point where increasingly, AI-powered agents will have the capabilities that make them indispensable to knowledge workers. This opens the door for Agentic Automation – a new level of AI support from which employees and companies will be able to benefit reliably for the first time.
Dubai — UiPath, a leading agentic automation and AI company, sheds light on what to expect in the coming year in its AI and Automation Trends 2025 report. UiPath’s predictions are based on extensive market analysis, current developments in AI research and experience from working with over 10,000 companies worldwide.
“AI has long since left the status of a trend behind. 2025 will be the year in which it establishes itself as an indispensable work tool in many industries through agent-based automation,” says Zakaria Haltout, Area Vice President MEA at UiPath. “The latest Astra Tech study reveals that in the MEA region, 65% of organizations are prioritizing AI-driven strategies, particularly in finance, government, and healthcare. As companies focus on addressing scalability and integration challenges, Agentic AI is poised to accelerate digital transformation and redefine operational efficiency.”
Autonomy within orchestration
The trends that lie ahead are undoubtedly linked to the development of technology. It is therefore a good place to start when analyzing the expected direction its use will take.
Trend I. The rapid development of AI agents that autonomously understand, plan and operate within complex workflows.
Prediction: Agent-based AI will allow companies to automate complex processes with minimal supervision, increasing productivity and opening up new opportunities for industry-specific automation solutions.
Preparation: Subject at least one process to agent automation. Passivity stifles innovation, so it is worth joining the pioneers in agentic AI or at least keeping a close eye on their activities.
Trend II. With the development of agent-based artificial intelligence, orchestration is becoming increasingly important.
Prediction: In order to realize the full potential of agentic AI, businesses will need a dynamic infrastructure that enables humans and robots to collaborate with agents. Additionally, it will need to enable their creation, deployment, as well as monitoring of their activities with transparency and compliance.
Preparation: Create a plan for the introduction and scaling of an agentic AI environment, taking into account the need for human oversight and the role of RPA robots as the ‘hands and feet’ of new agents.
New business strategies
Next year’s changes will not only affect the technology behind AI itself, but also the ways in which it can be used in a business context. Organizations will be rethinking how they approach problems such as technology debt or the lack of a concrete strategy when implementing AI.
Trend III. Executives are disillusioned with spending millions on AI without the expected results. Companies that implement AI without clear strategies to measure and demonstrate ROI will struggle to justify the costs.
Predicion: Companies need to develop procedures to track and measure the impact of AI on key business outcomes such as productivity, cost savings and revenue growth. The role of business technology providers will also increase. One of the most widespread uses of AI are ‘copilots’, which help employees with various office tasks. These are being developed by major enterprise technology providers such as Microsoft, GitHub and Google and are yielding excellent results. For example, UiPath has created Autopilot for Developers, which reduces automation development time by 75%.
Preparation: A greater focus on AI ROI measurement tools and strategies, a thorough analysis of the company’s use of the technology and training in the use of embedded tools such as copilots.
Trend IV. Heads of technical departments are turning to AIOps (Artificial Intelligence for IT Operations) tools to streamline operations, automate routine tasks and improve system reliability.
Prediction: As organisations increasingly rely on complex digital infrastructures, many are struggling with technology debt – accumulated inefficient processes and outdated systems that can slow down innovation or increase the cost of operations.
Preparation: Investing in AIOps can prove invaluable for managing technology ecosystems more effectively. This will reduce short- and long-term technology debt, while freeing up resources to drive innovation.
Regulatory landscape
Trend V. Escalating regulation: global lawmakers are working to control the power of AI.
Prediction: The AI Act introduced by the European Union could result in the first fine related to artificial intelligence. The EU is spearheading the introduction of increasingly restrictive regulations on the technology. This could discourage investment in AI within the EU and stifle growth, or alternatively become a model for legislation in the US, UK and Asia-Pacific, which the AI research communities are still waiting for.
Preparation: Implement robust data governance and adequate security measures, prioritise transparency as well as comprehensibility of AI algorithms and establish clear accountability structures for AI-related decisions.
