The research, by the thought leadership and research arm of Infosys, Data+AI Radar: Making AI Real, found that although three of four companies want to operate AI across their firms, most businesses are new to AI and face daunting challenges to scale. 81% of respondents deployed their first true AI system in only the past four years, and 50%, in the last two.
The report, which surveyed 2,500 senior technology leaders and executives across 13 industries across the US, UK, France, Germany, Australia, and New Zealand, also found that 63% of AI models function only at basic capability, are driven by humans, and often fall short on data verification, data practices, and data strategies. Only 26% of practitioners are highly satisfied with their data and AI tools. Despite the siren song of AI, something is clearly missing.
Infosys Knowledge Institute found that high-performing companies think differently about AI and data. It also found leaders focus in three areas:
- Transform data management to data sharing. Companies that embrace the data-sharing economy generate greater value from their data. Data increases in value when treated like currency and circulated through hub-and-spoke data management models (US$105bn incremental value). Companies that refresh data with low latency generate more profit, revenue, and subjective measures of value.
- Move from data compliance to data trust. Companies highly satisfied with their AI (currently only 21%) have consistently trustworthy, ethical, and responsible data practices. These prerequisites tackle challenges of data verification and bias, build trust, and enable practitioners to use deep learning and other advanced algorithms.
- Extend the AI team beyond data scientists. Businesses that apply data science to practical requirements create value. The report found that business—data scientist integration accelerates efficiencies and value extraction (additional $45 billion profit growth). For intelligent data, business and IT are much better together.
Infosys says that combined, these areas not only scale AI usage but unlock its potential value – transforming AI dreams to insights and operational effectiveness and improving the human experience.
Source: Infosys Knowledge Institute / AI