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The impact of AI on process analyst skills

Discover the skills process analysts should learn now to be successful in the future

Inefficiency is the enemy of any business. Whether a company is working to better understand its audience, conceptualize and develop new products, or market its services, its processes play a major part in determining its success. Process analysts have traditionally taken the lead in understanding and streamlining these processes. But with the increasing prevalence of artificial intelligence (AI), the role of process analysts may be changing.

To help process analysts understand these changes, ServiceNow recently partnered with Pearson to take a closer look at the effects of AI technology. Their research addresses the future of process analysts and seven other technology-focused professions, predicting how these roles will evolve alongside emerging AI and automation technologies in the next five years.

This research paints a bright future for process analysts. It is anticipated that by 2027 the demand for process analysts will surge, creating approximately 65,000 process analyst jobs in the U.S. alone. That said, tomorrow’s analysts may enter a very different job market from the one we have today. To remain relevant in the face of changing information technologies, process analysts must adapt.

Business processes are most effective when they are optimized in terms of cost and time. Process analysts work with these processes to identify areas that need improvement. Specifically, the role of a process analyst involves systematically examining and documenting the various steps in a process, as well as analyzing relevant data to identify inefficiencies, bottlenecks, and potential issues. Process analysts rely on a range of tools and techniques, including process mapping and statistical analysis, and often work with various teams and departments to better understand processes, implement changes, and track those changes over time.

Process analysts have the responsibility of making business processes and workflows as efficient as possible. In the United States, process analysts earn an average annual salary of $66,500.

Analyzing business processes demands a diverse skill set. Core capabilities needed for this position include: 

  • Experience with business intelligence (BI) tools (Tableau, Alteryx, etc.)

  • Understanding of relevant technologies (ERP systems, workflow software, data analytics tools, etc.)

  • Proficiency in data analysis (for working within multiple systems and applying various data transformation methodologies) 

  • Analytical skills (to identify problems, opportunities, and possible solutions)

  • Communication skills (for collaborating with stakeholders)

  • Data gathering expertise (decision-making and continuous-improvement efforts)

  • Familiarity with project management methodologies (for planning, executing, and monitoring process improvement initiatives)

  • Knowledge of data-management regulations (to ensure regulatory compliance)

Within the next five years, the rapid growth of AI is poised to have a noticeable effect on the role of process analysts. Advanced technologies will equip analysts with robust tools, enabling them to efficiently streamline business processes at scale.


But unlike many technical positions, none of the process analyst's primary tasks is expected to become fully AI automated. Consequently, process analysts are set to benefit from approximately 3.3 hours of increased weekly capacity due to the emergence of intelligent technologies. Overall, it's expected that 16 process analyst tasks could be at least partially augmented by AI and automation within five years. 

The four key technologies driving this transformation are:

Predictive analysis: Tools that reactively use machine learning (ML) to conduct narrow analysis and make related predictions

Solution discovery: Agents using reinforcement learning (RL) and sensors to digest and solve unstructured, complex problems

Collaborative robotics: Robots using RL and sensors to co-contribute to generating shared meaning

According to the ServiceNow/Pearson study, AI augmentation is projected to play a part in 18.8% of process analyst tasks by 2027

Decision generation: Systems that use ML to evaluate input data to determine the best course of action

Moreover, the study reviewed six process analyst tasks that will likely experience some level of transformation due to AI and automation. Among these activities, three were predicted to be most significantly affected:

1. Performing data gathering, root cause analysis, and performance trending to develop appropriate process control changes

2. Coordinating with subject matter experts to develop process improvement reports for setting forth progress, adverse trends, and appropriate recommendations and conclusions

3. Informing respective teams on process improvements and reengineering strategies

Although the role of process analyst will likely experience less disruption than many other technology-based roles, AI and automation will still necessitate a shift in terms of skills. 

Adapting to meet the needs of the new AI-enhanced workplace will demand collaboration between process analysts and leadership. Decision-makers will need to take an active role in developing relevant and comprehensive training programs to help ensure that today’s analysts have the education and support they need to make the transition into tomorrow’s workforce. 

The ServiceNow/Pearson study identified five capabilities that will demand the highest levels of proficiency from process analysts by 2027:

1. Developing keen innovation and entrepreneurship skills

2. Focusing on achievements

3. Increasing focus on personal learning and mastery

4. Improving judgment and decision-making capabilities

5. Collaborating and communicating effectively across digital media

As new AI technologies redefine how organizations handle crucial tasks, process analysts remain a vital force in ensuring process efficiency. In the coming years, these analysts will utilize advanced AI capabilities to enhance their productivity and value delivery, further streamlining important processes to match business growth. In order to facilitate this transition, IT leaders must identify skills gaps, understand the evolving proficiency requirements, and establish suitable training and upskilling programs to prepare their workforce for an AI-driven future. 

After all, inefficiency is the enemy of business. With emergent automation technologies, process analysts will have the resources they need to turn every business process into a seamless experience.

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