Currently, much is being said about Artificial Intelligence (AI) and the benefits it has brought to various sectors and companies. However, operational maturity in AI of a company is important for several reasons. Firstly, it allows for a precise assessment of the starting point, helping to identify where the company stands in relation to best practices and the state of the art.
Operational maturity in AI refers to the level of development and integration of artificial intelligence technologies within an organization. This concept encompasses a company’s ability to adopt and use artificial intelligence effectively to improve processes, make data-driven decisions, and innovate in its products and services.
Companies with high maturity not only implement advanced technologies but also cultivate an organizational culture that values data and insights, has a robust technological infrastructure, and has teams trained to explore the full potential of artificial intelligence. Achieving operational maturity involves a continuous process of technological evolution, strategic adaptation, and the development of internal competencies.
A survey by McKinsey shows that companies with high maturity in artificial intelligence have 3 to 5 times more chances of being leaders in their respective industries. Furthermore, data from Deloitte states that companies in more advanced stages of AI maturity can increase productivity by up to 40%.
This evaluation also facilitates the efficient allocation of resources, allowing the company to focus its efforts on areas that need the most development. By identifying gaps and opportunities, the organization can prioritize initiatives that will bring greater impact and value.
A study by Forrester reveals that 56% of companies consider measuring maturity essential to optimizing investments and improving operational effectiveness. With an assessment of operational maturity, it is possible to develop a detailed and structured roadmap for AI adoption, including phases, milestones, and success metrics that will guide implementation in an orderly and strategic manner.
What are the benefits of measuring AI maturity?
Furthermore, measurement facilitates the necessary cultural change in the organization, promoting a culture of innovation and adaptation. ‘Continuously monitoring maturity allows adjusting strategies as needed, ensuring continuous and sustained improvement in AI adoption. It also helps mitigate risks by anticipating and avoiding issues that could compromise project success,’ says Business Director at Keyrus, Paulo Simon.
Companies with a high level of maturity are better positioned to take advantage of the competitive advantages that technology offers. Assessing and improving this operation helps the company to stay competitive and fully exploit its potential. According to PwC, the effective adoption of AI can add up to $15.7 trillion to the global economy by 2030. Finally, ensuring that the tool is aligned with the company’s strategic objectives ensures that the efforts contribute directly to business goals and generate tangible value.
For Paulo, measuring operational maturity is essential for effective and strategic adoption of technology, ensuring that the company is well prepared to face challenges and seize the opportunities that artificial intelligence offers.
Stages of operational maturity in AI
- Initial Recognition
- Awareness culture: The company promotes an internal culture of awareness about the concepts and benefits of artificial intelligence and machine-generated artificial intelligence (GenAI).
- Education and training: Initiatives for education and training for employees at all levels are carried out to increase understanding of AI/GenAI and its potential impact on business.
- Feasibility assessment: The company conducts preliminary assessments to identify potential areas where implementation can bring significant benefits.
- Sectoral Implementation
- Implementation Strategy: The company develops a clear strategy to implement AI/GenAI in specific areas, aligned with its business objectives and overall strategy.
- Integration with Existing Processes: AI/GenAI is smoothly and efficiently integrated into the company’s existing processes, optimizing workflows and improving operational efficiency.
- Impact Measurement: KPIs and metrics are established to measure the impact of implementation, including increased efficiency, cost reduction, and improved customer experience.
- Initial Exploration
- Controlled Experimentation: Controlled experiments and pilot projects are conducted to explore applicability and feasibility in real business scenarios.
- Results Evaluation: The results of pilot projects are rigorously evaluated to determine success and effectiveness in achieving defined business objectives.
- Feedback and Learning: The company leverages feedback from pilot projects to learn and adjust its approach as it continues to explore the tool.
- Organizational Expansion
- Governance and Change Management: The company implements a robust and effective governance framework to oversee the expansion of AI/GenAI throughout the organization and manage the associated organizational change effectively.
- Investment in Infrastructure and Talent: Significant investments are made in technological infrastructure and in the hiring and development of specialized talent in the field.
- Scalability Strategy: The strategy is designed to scale effectively throughout the organization, ensuring systems handle increased workloads.
- Advanced Operations
- Holistic Automation: It is integrated into all aspects of the company’s operations, covering from internal processes to interactions with customers and partners.
- Data-Driven Decision Making: Decisions are informed by data and insights generated by algorithms, resulting in more accurate and effective decisions.
- Continuous Innovation: The company adopts a continuous innovation approach, constantly exploring new applications and advancements to maintain a competitive edge.
- AI/GenAI Leadership
- Culture of Innovation: The company nurtures a culture of innovation and experimentation, where the use of AI/GenAI is encouraged and valued at all levels of the organization.
- Strategic Partnerships: Strategic partnerships are established with market leaders to access specialized knowledge, resources, and cutting-edge technologies.
- Future Vision: The company maintains a future vision, constantly exploring the frontiers of technology and seeking ways to apply AI to create new business models and transform entire sectors.
Measuring operational maturity is crucial for companies to position themselves competitively in the current market. Understanding the current stage and charting a strategic path optimizes resources and maximizes results.
By following the six stages of maturity, companies can evolve from initial awareness to strong AI leadership, ensuring successful adoption and fostering a culture of continuous innovation. “This structured approach mitigates risks and enables capitalizing on the opportunities offered by artificial intelligence, making measurement an essential strategy for sustainable growth and future success,” concludes Simon.
