We already know that AI contributes in numerous ways to organizational routines and the optimization of results. But can it also impact process management maturity?
Process management maturity indicates the level of structuring, documentation, control, and optimization of a company’s workflows, demonstrating its ability to deliver consistent, efficient, and predictable results.
It can also be used to assess the degree of control and governance over an organization’s processes—evaluating how well they are organized, how improvements are implemented, and whether their focus remains aligned with overall strategic objectives.
Artificial Intelligence, when combined with process management, plays a strategic role in driving continuous improvement and process optimization. It also supports the implementation of automation, making processes more agile, among many other advantages.
Therefore, it is clear that AI can positively impact an organization’s process management maturity. To better understand how this happens in practice, let us explore the advantages and benefits of using AI in process management.
Advantages of Using AI in Process Management
Artificial Intelligence enhances process management in organizations through three core pillars:
- Task and operations automation;
- Monitoring and forecasting;
- Strategic focus.
When incorporated into daily operations, AI can accelerate tasks, predict failures, and support strategic decision-making.
Task automation, for example, ensures less bureaucratic routines. Monitoring, in turn, enables the analysis of larger volumes of data in less time, facilitating the adoption of predictive strategies to anticipate market trends and potential incidents or failures.
As a result, employees are freed up to focus on more strategic activities, ensuring greater agility in processes and more data-driven decision-making.
All of this contributes to faster customer service and, consequently, higher levels of customer satisfaction with the products or services offered by the organization.
AI and Process Management Maturity
In practice, when we relate the improvements achieved through the use of AI to maturity levels, it becomes clear that progress can be made across all scenarios.
– Initial Level
Scenario: Indicates a management model with a low level of organization, considered unstructured. Employees do not follow a standard for performing the same activities or for documentation.
What to do to evolve: Map existing processes, document routines, assign responsibilities, train teams, and monitor execution.
How AI contributes: AI can support process mapping and the creation of standardized documentation by suggesting workflows and generating documents based on them.
– Managed or Repeatable Level
Scenario: Indicates that the organization has advanced in maturity, with processes that produce predictable, consistent, and repeatable results. However, not all employees are familiar with these processes and documents, leaving room for errors and inconsistencies.
What to do to evolve: Transform isolated knowledge into formal standards. Standardize workflows, validate documentation, align organizational culture, and adopt technology.
How AI contributes: AI can accelerate this transition by transforming operational data into predictive insights, enabling management to evolve into an agile, autonomous ecosystem focused on continuous innovation. It can analyze mapped workflows, suggest improvements, eliminate repetitive tasks, and automate processes to reduce errors.
– Defined Level
Scenario: The main characteristic of this level is the existence of standardized and documented internal routines defined by responsible managers. However, knowledge of these routines is still limited to those directly involved, even in multidisciplinary processes.
What to do to evolve: Focus on performance measurement and the use of quantitative metrics. Implement KPIs, systematically collect data, and train teams. The use of software becomes essential.
How AI contributes: AI can suggest KPIs aligned with business and process objectives, collect and analyze data more quickly to identify bottlenecks or failures, and automate tasks.
– Predictable Level
Scenario: This level is characterized by the ability to measure and analyze processes, as well as compare them with competitors and industry leaders.
What to do to evolve: Institutionalize continuous process adaptation and adopt advanced technologies. Focus on innovation, workflow redesign, advanced data usage, and strengthening a culture of continuous improvement.
How AI contributes: AI can support predictive analytics, intelligent process mining, and adaptive workflow management, while enhancing data-driven decision-making.
– Optimized Level
Scenario: This is the highest level, referring to organizations where processes are already in a state of continuous improvement. Due to their maturity, errors can be quickly corrected and documentation updated accordingly.
What to do to sustain: Proactively consolidate continuous improvement. Corporate governance must remain aligned with strategy, monitoring should occur in real time through performance indicators, and a culture of innovation must be reinforced to prevent operational setbacks.
How AI contributes: AI helps sustain the highest level of maturity by automating real-time monitoring, predicting bottlenecks through advanced analytics, and suggesting continuous improvements based on collected data—transforming the BPM cycle into an adaptive and proactive system.
AI Tools Available in Interact BPM
Interact BPM, a process management solution within the Interact Suite, promotes alignment between organizational strategies, information technology, and operational technologies. It also features artificial intelligence tools specifically designed to accelerate the creation of process steps.
With the Interact Process Assistant, AI works in your favor to optimize processes. Through a simple chat interaction, it provides intelligent suggestions to improve workflows, such as:
- Identifying steps that can be removed;
- Recommending improvements and optimization opportunities;
- Generating a complete model from a simple title and description.
The Modeling Assistant not only generates models based on a process description summary but also identifies potential improvements within the model, suggests performance indicators for accurate monitoring, and produces a critical analysis based on process data.
In Interact Governance, also available within the Interact BPM solution, artificial intelligence tools support the company’s strategic framework by generating recommendations, indicators, and action plans aligned with methodologies such as BSC and OKR.
Would you like to explore the full solution and its benefits?
Click here to discover everything Interact BPM can do to elevate your organization’s process management maturity.
Extra: Identify Your Company’s Maturity Level for Free
Interact Flow, a solution developed by Interact, offers a free Process Management Maturity Model inspired by the framework created by Pedro Robledo, a BPM expert, President and Co-founder of ABPMP Spain, and a professor at the International University of La Rioja (UNIR).
The assessment questionnaire is based on seven fundamental pillars, dynamically interconnected to ensure a thorough analysis of any organization.
After completing the questionnaire, the solution provides AI-powered tools that can recommend actions to support the advancement of your organization’s processes across maturity levels.
Click here, sign up, and start your assessment today!
