Accenture and the Carnegie Mellon University Software Engineering Institute (SEI) have come up with a research-validated approach, the AI Adoption Maturity Model, which is designed for commercial and governmental entities interested in scaling beyond the experimentation phase of AI implementation to tangible results that can be reliably replicated. While 86% of corporate executives are planning on increasing spending on artificial intelligence technology, current progress is slow; only 21% are engaging in re-engineering business processes, while about half note negligible profits from the use of the technology due to misalignment of expectations and flawed approaches to implementation. Leveraging over 11,000 AI projects executed by Accenture and decades-long expertise in SEI’s maturity models, this engineering-focused framework breaks down AI capabilities into eight dimensions: organizational strategy, workforce and culture, re-engineered workflow, risk and governance, data, engineering, operations, and ecosystem.
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This model was empirically developed through reviews of over one hundred frameworks, executive interviews conducted with 25 leaders, survey of almost 600 experts, and pilots with Fortune 500 companies. With the help of benchmarking tools and roadmap for implementation, the framework allows companies to create a benchmark of their readiness level and understand what types of applications will be beneficial for them. Commenting on the necessity of this operational foundation, Manish Sharma, Chief Strategy and Services Officer at Accenture, noted, “Many AI maturity models in the market now focus on high-level strategy without considering the engineering rigor that organizations actually need to scale.”
