AI Research Team

The art of AI maturity: Advancing from practice to performance

As artificial intelligence becomes increasingly important in today’s digital landscape, understanding and implementing AI strategies is essential for businesses looking to stay competitive and innovative. In this research, we’ll dive into the world of AI maturity, its benefits, and the key factors that set AI Achievers apart.

How prepared is your organization to harness the power of AI and stay ahead of the competition?

Innovative technologies, such as 5G, AI, and cloud computing, are reaching critical junctures for widespread implementation. According to Harvard Business Review, their research demonstrates that by 2025, organizations plan to transition approximately 60% of their IT infrastructure to the cloud. Furthermore, over 50% of businesses have already incorporated AI into at least one aspect of their operations.

Although boards may be inclined to prioritize cost reduction or maintain limited IT investments, it is essential that they also emphasize the importance of capitalizing on opportunities to invest in future technologies.

By doing so, they can ensure their businesses remain relevant and enhance productivity. As such, boards must strike a balance between addressing immediate financial concerns and recognizing the potential risks and rewards associated with significant technological shifts.

By 2025, the norm will be intelligent workflows and fluid collaboration between humans and machines, with data-driven optimization pervading nearly all aspects of work.

businessman businesswoman working in an organization improving ai solutions

What is AI maturity?

AI maturity encompasses the extent to which an organization has developed, integrated, and capitalized on artificial intelligence technologies.

Key factors include the adoption of AI solutions, successful deployment across diverse business functions, and the utilization of AI for informed decision-making and innovation. Organizations with a high level of AI maturity, often referred to as AI achievers, demonstrate expertise in leveraging AI to foster growth, efficiency, and competitive edge.

AI Maturity Defined:

AI maturity gauges the extent to which organizations have acquired AI-related capabilities in the appropriate combination to deliver high performance for customers, shareholders, and employees.

Four levels of AI maturity have been identified:

Data Foundation,” “Advanced Analytics,” “Integrated Intelligence,” and “Autonomous.” At the lowest level, “Data Foundation,” companies are using basic data analytics and reporting to gain insights into their operations. At the highest level, “Autonomous,” companies are using AI to automate decision-making and other business processes.

The benefits of progressing up the AI maturity ladder are significant. As companies move from one level to the next, they gain more advanced capabilities, such as predictive modeling, natural language processing, and computer vision. These capabilities can lead to improved efficiency, better decision-making, and enhanced customer experiences.

For example, a company at the “Integrated Intelligence” level can use AI to personalize marketing messages and product recommendations for individual customers, while a company at the “Autonomous” level can use AI to optimize supply chain management and reduce costs.

However, achieving AI maturity is not a straightforward process. It requires careful planning, investment in technology and talent, and a clear understanding of the business problems that AI can solve. In the next section, we will discuss the challenges and risks associated with AI transformation and how to address them.

Deploy.ai has identified several of these challenges and risks:

1. Data Privacy and Security

AI relies on vast amounts of data, raising concerns about data privacy and security. Companies must ensure that their data handling practices comply with regulations and industry standards and have appropriate safeguards in place to protect sensitive data.

2. Lack of Skills and Resources

Developing and implementing AI solutions require specialized skills and expertise that may be difficult to find in the workforce. Companies may need to invest in training and development programs to build the necessary skills or partner with external experts.

3. Ethical Considerations

As AI becomes more advanced, ethical considerations must be addressed by companies. Ensuring AI solutions are fair and unbiased, and do not perpetuate or exacerbate social inequalities is essential.

4. Integration with Existing Systems

Integrating AI solutions with existing systems and processes can be challenging, especially for companies with complex legacy systems. Companies must ensure their AI solutions work seamlessly with their existing technology and processes without disrupting operations.
To address these challenges and risks, companies must take a strategic approach to AI transformation.

Developing a clear understanding of the potential benefits and risks of AI and creating a comprehensive AI strategy that considers these factors is crucial. In the next section, we will discuss how to build an effective AI strategy.

Research Reveals

AI maturity hinges on effectively combining key capabilities in data, AI, organizational strategy, talent, and culture. This includes:

  • Foundational AI capabilities – cloud platforms, data platforms, architecture, and governance – which are essential to staying competitive.
  • Differentiation AI capabilities – AI strategy, executive sponsorship, and an innovative culture – which can set businesses apart and drive success.


Only 12% of companies are AI Achievers

“How does your company’s AI maturity compare to that of AI Achievers?”

Building an Effective AI Strategy

1. Define the Business Problem

The first step in developing an effective AI strategy is to define the business problem that AI can solve. Companies should identify specific areas of their business where AI can add value, such as improving customer experience, increasing efficiency, or reducing costs.

2. Set Goals and Objectives

Once the business problem has been defined, companies should set clear goals and objectives for their AI strategy. These goals should be aligned with the overall business strategy, and they should be measurable and achievable.

3. Select the Right Technology and Tools

There are many different AI technologies and tools available, and companies must select the ones that are best suited to their specific needs. This may include machine learning algorithms, natural language processing tools, or computer vision technologies.

4. Build a Data Infrastructure

AI relies on vast amounts of data, so companies must build a data infrastructure that is capable of collecting, storing, and processing large volumes of data. This may require investments in cloud computing, data analytics, or other technologies.

5. Develop a Roadmap

Once the key components of the AI strategy have been defined, companies should develop a roadmap for implementation. This roadmap should include specific milestones, timelines, and resources required for each phase of the implementation process.

By following these key components, companies can develop an effective AI strategy that addresses their specific business needs and enables them to achieve AI maturity and transformation. However, it is important to note that AI transformation is not a one-time event, but rather an ongoing process of continuous improvement and adaptation. In the next section, we will provide examples of organizations that have successfully achieved

The potential for AI expansion across various industries is immense, presenting a remarkable opportunity for businesses ready to harness its power.

AI Achievers are revolutionizing industries by deploying AI solutions to tackle challenges, seize opportunities, and outperform competitors. They have transcended the AI agenda’s cost-saving aspects to fuel growth and innovation, with their AI-driven revenues accounting for over 30% of their total revenues – a remarkable 3.5 times more than Experimenters.

AI Achievers excel in the following areas compared to other groups:

1. Holistic Performance Excellence

These companies exhibit exceptional performance across a blend of capabilities. Their prowess lies not in the sophistication of a single capability, but in their ability to synergize strengths across strategy, processes, and people.

2. Consistent Scaling of AI Solutions

AI Achievers move beyond experimentation and apply AI to solve critical business challenges. They are more likely to scale AI pilots across the enterprise compared to Experimenters, ensuring AI plays a crucial role in their operations.

3. Emphasis on Non-Financial Metrics

They outperform other groups on environmental, social, and governance (ESG) and customer metrics. AI Achievers are more likely to rigorously measure and reduce their greenhouse gas emissions, consume natural resources economically, and employ AI responsibly. They also prioritize building strong customer relationships, fostering trust, minimizing churn, and enhancing the quality and safety of their offerings.

As AI experts, AI Achievers showcase the transformative power of artificial intelligence when implemented strategically and responsibly, serving as an inspiration for businesses aspiring to harness the full potential of AI.

AI Achievers Advancing Industries

AI Achievers are revolutionizing industries by deploying AI solutions to tackle challenges, seize opportunities, and outperform competitors. They have transcended the AI agenda’s cost-saving aspects to fuel growth and innovation, with their AI-driven revenues accounting for over 30% of their total revenues – a remarkable 3.5 times more than Experimenters.

AI Achievers excel in the following areas compared to other groups:

1. Holistic Performance Excellence

These companies exhibit exceptional performance across a blend of capabilities. Their prowess lies not in the sophistication of a single capability, but in their ability to synergize strengths across strategy, processes, and people.

2. Consistent Scaling of AI Solutions

AI Achievers move beyond experimentation and apply AI to solve critical business challenges. They are more likely to scale AI pilots across the enterprise compared to Experimenters, ensuring AI plays a crucial role in their operations.

3. Emphasis on Non-Financial Metrics

They outperform other groups on environmental, social, and governance (ESG) and customer metrics. AI Achievers are more likely to rigorously measure and reduce their greenhouse gas emissions, consume natural resources economically, and employ AI responsibly. They also prioritize building strong customer relationships, fostering trust, minimizing churn, and enhancing the quality and safety of their offerings.
As AI experts, AI Achievers showcase the transformative power of artificial intelligence when implemented strategically and responsibly, serving as an inspiration for businesses aspiring to harness the full potential of AI.

Creating The Right Steps to Improve Your AI Maturity

Leveraging partnerships is crucial for businesses aiming to achieve AI maturity. Establishing collaborations with AI solution providers, research institutions, and industry consortia can help access specialized knowledge, resources, and expertise that might not be available in-house. Forming strategic partnerships can accelerate your AI initiatives and contribute to overall AI maturity.

Leverage Partnerships For AI Success

Establish Strong AI Partnerships

Collaborate with AI solution providers, research institutions, and industry consortia to access specialized knowledge and resources for AI maturity.

Build a Collaborative Ecosystem

Identify suitable partners, create a supportive ecosystem, and work closely to develop tailored AI solutions for organizational goals.

Jointly Develop and Implement AI Solutions

Regularly evaluate partnership success, adapt to changing needs, and explore new collaboration opportunities for continuous growth.

Final Thoughts

In conclusion, achieving AI maturity and transformation is critical for businesses in the digital age. By understanding the levels of AI maturity, the challenges and risks associated with AI transformation, and the key components of an effective AI strategy, companies can develop a roadmap for achieving AI maturity and transformation.

An effective AI strategy requires a clear understanding of the business problem that AI can solve, setting clear goals and objectives, selecting the right technology and tools, building a data infrastructure, and developing a roadmap for implementation. By following these key components, companies can develop an AI strategy that is tailored to their specific needs and objectives and enable them to achieve AI maturity and transformation.

The examples provided in this post demonstrate that AI transformation is possible and can deliver real value to businesses. From improved decision-making and customer experience to enhanced marketing and customer service, AI has the potential to transform every aspect of a business.

However, it is important to note that AI transformation is an ongoing process that requires continuous improvement and adaptation. Companies must be willing to invest in technology and talent, address the challenges and risks associated with AI, and embrace a culture of innovation and experimentation to achieve AI maturity and transformation.

In the end, AI transformation is not just about technology; it’s about reimagining how businesses operate and how they deliver value to their customers. By taking a strategic approach to AI, companies can unlock the full potential of this powerful technology and gain a competitive advantage in the digital age.

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AI Research Team

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