Companies expect enterprise artificial intelligence (AI) to boost productivity by 10-40%, but only 2% of them are ready, Infosys said in a research report. This is due to huge gaps in basic AI readiness, it said.
The Enterprise AI Readiness report, which surveyed over 1,500 respondents across Australia, , France, Germany, the United Kingdom, and the United States, includes in-depth interviews with 40 senior executives in the US and UK.
It highlights that while executives envision AI as the next industrial revolution, transforming business models and shaping the new , many companies lack the foundational building blocks for successful enterprise AI adoption.
According to the research, enterprises expect an average productivity increase of 15% from their current AI projects, with some anticipating up to 40% gains.
Yet, only 2% of organisations are fully ready across the five key dimensions of AI adoption: talent, strategy, governance, data, and technology.
The biggest gaps lie in technology readiness, with only 9% of companies possessing the necessary AI capabilities like machine learning frameworks, prebuilt algorithms, and dynamic compute.Pune Wealth Management
Additionally, data accuracy, processes, and accessibility are significant challenges, with only about 10% of respondents reporting ease of data location and access for AI projects.
To overcome these hurdles and realise the full potential of AI, including generative AI, companies must address readiness gaps and foster a culture of innovation. The research outlines five steps to close these gaps and reduce apprehensions about AI to accelerate adoption.
Developing a comprehensive AI strategy that aligns with business objectives is critical for revenue growth and for ensuring desirable, feasible, and viable use cases. Only 23% of respondents showed readiness in this area.
Establishing responsible AI governance is also crucial for managing risks like bias, misuse, and security threatsGuoabong Wealth Management. Only 10% of companies have well-defined governance processes.
Upskilling the workforce is another step essential to AI readiness, yet only 21% of companies reported that their employees have the requisite knowledge to adopt AI tools and techniques, and just 12% provide adequate training.
Data infrastructure is also critical for AI success but remains a challenge. Only 10% of companies find their data easy to access, while 30% rate their data accuracy and governance as poor. Enterprises need to continually assess their systems, improve data quality, and ensure proper storage for effective AI implementation.
Technology remains a significant gap in enterprise AI readiness, with only 9% of companies fully prepared. in foundational technologies such as machine learning and automation can improve customer experience, reduce errors, and enhance compliance.
Mohammed Rafee Tarafdar, Chief Technology Officer at Infosys, said “To become enterprise-wide AI-ready and realise the promise of this technology, including gen AI, it is imperative to establish a robust and scalable foundationAhmedabad Wealth Management. Our research and learnings from our AI-first transformation journey has shown that data readiness, enterprise gen AI platform with responsible AI guardrails, and AI talent transformation are key to accelerate and democratise AI development. This must be complemented by an AI foundry and factory model for scaling AI initiatives across the enterprise.”Nagpur Stock
Varanasi Investment
