AI assessment benchmarks

Discover how your organisation stacks up against industry standards across 8 key areas of AI maturity.

Benchmark areas

Our benchmarks are drawn from industry-leading reports, research studies, and our extensive experience in AI consulting.

1. Strategic alignment

2. Digital maturity

3. AI knowledge and skills

4. Operational efficiency

5. Innovation and continuous improvement

6. Client engagement and service delivery

7. AI integration and usage

8. Data management and analytics

1. Strategic alignment

Companies that excel in aligning AI with their business strategy often see a 30% increase in efficiency and a 20% increase in revenue.This alignment is critical for leveraging AI to achieve business objectives.

Level 4

‍

Description

AI strategy well-aligned with overall business strategy.

Typical scores

Most SMEs are at 2 (Fair) or 3 (Good), with leading firms reaching 4 (Very Good)
(Source: Digital Maturity Benchmark)

2. Digital maturity

According to a McKinsey report, leading companies have integrated digital tools across all aspects of their operations, achieving digital maturity levels of 4 to 5. They use advanced technologies such as cloud computing, IoT, and AI to enhance their operations.

Level 4

‍

Description

Extensive use of digital tools; well-integrated systems.

Typical scores

Most SMEs score between 2 (Emerging) and 3 (Connected), with digital leaders reaching 4 (Multi-moment)
(Sources: Digital Maturity Benchmark, Digital Adoption)

3. AI knowledge and skills

According to the AI Index 2022 report, organisations in the top quartile have over 40% of their workforce trained in AI and machine learning. These firms frequently offer continuous learning and development opportunities to maintain their competitive edge.

Level 3

‍

Description

Moderate knowledge; some team members have received training.

Typical scores

Many SMEs fall between 1 (Poor) and 2 (Fair), with tech-savvy firms reaching 3 (Good)
(Source: MDPI)

4. Operational efficiency

Research by Deloitte shows that organisations with high levels of automation report a 60% reduction in process cycle times and a 50% improvement in operational efficiency. These companies use AI and RPA extensively to optimise their processes.

Level 4

‍

Description

AI-deployment well aligned with business processes.

Typical scores

SMEs generally score 2 (Fair) to 3 (Good), with efficient firms reaching 4 (Very Good)
(Sources: Digital Adoption, Deloitte United States)

5. Innovation and continuous improvement

A study by Accenture indicates that firms with a strong focus on innovation and continuous improvement driven by AI are 2.5 times more likely to be leaders in their industry. These companies continually experiment with new AI technologies to stay ahead.

Level 4

‍

Description

Strong focus on innovation; continuous improvement culture.

Typical scores

SMEs often score between 1 (Poor) and 3 (Good), with innovative companies reaching 4 (Very Good)
(Source: SimilarWeb)

6. Client engagement and service delivery

According to Forrester, companies using AI to enhance client engagement see a 50% increase in customer satisfaction and a 40% increase in client retention rates. They utilize AI-driven CRM systems to deliver personalized experiences.

Level 4

‍

Description

Advanced AI tools used to personalise and improve client services.

Typical scores

Scores typically range from 2 (Fair) to 3 (Good), with advanced firms achieving 4 (Very Good)
(Source: MDPI)

7. AI integration and usage

A survey by MIT Sloan Management Review found that 45% of the most digitally mature companies have extensively integrated AI across multiple business functions compared to only 10% of the least mature companies.

Level 3

‍

Description

Moderate use of AI in specific areas.

Typical scores

SMEs typically score between 1 (Poor) and 2 (Fair), with innovative firms achieving 3 (Good)
(Sources: Deloitte United States, MDPI)

8. Data management and analytics

Gartner indicates that top-performing firms have robust data management practices, with 75% of them leveraging advanced analytics and data-driven decision-making. These companies often employ predictive analytics and real-time data insights to drive their business strategies.

Level 4

‍

Description

Advanced data analytics capabilities; data-driven decision-making.

Typical scores

SMEs generally score between 1 (Poor) and 3 (Good), with progressive companies reaching 4 (Very Good)
(Sources: Digital Adoption, Deloitte United States)

Why us

Tailored expertise

Our mission is to empower businesses like yours to harness the full potential of AI. With our tailored solutions, we transform your strategies ensuring growth and innovation every step of the way.

Visionary leadership

As leaders in AI consulting for SME firms, our vision is clear: to lead the industry with innovative solutions and unwavering dedication to your success.

Trusted values

Our values drive everything we do. From innovation and integrity to collaboration and excellence, we prioritise transparency, honesty, and exceptional results in every project.

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