Thursday, 17 November, 2022
Making AI Real. From Data Science to Practical Business – Infosys
One of the most significant issues in AI/data science today is getting value back from data intelligence investment. Infosys has just released an extensive report from 2,500 AI practitioners highlighting this in detail, along with other interesting AI and data findings.
Report ideal for
- Leaders and managers – CIOs, CDOs, CTOs, AIOps, MLops and IT leaders
Key points
- 81% of businesses have deployed their first AI system in the past four years.
- 85% of companies not achieving advanced AI capabilities
- 63% of AI is humans driven
- Financial services are most satisfied with AI, and telecoms are least satisfied
- 49% of companies moving to centralised data
- 15% of companies think data verification and AI infrastructure are the top challenges
- 77% are confident in AI ethics
- 94% are confident with AI bias management
- 21% consider high cost as the biggest challenge to AI
- 67% use deep learning in 30% of their AI systems
- 48% of the AI budget was spent on AI implementation
Lots more…
Critical thinking and insights – For leaders, managers
Every AI should be focused on giving value and return on investment. The report states that companies can generate over $460 billion in incremental profit if they: Improve data practices, AI trust and integrate AI with their business operations. Many AI projects still need to catch up in data verification, data practices and data strategies. When all of these areas are addressed, it can help unlock the potential of AI.
Fundamentally, each project should focus on the business objectives. Every aspect should be aligned to point towards this.
Critical thinking and insights – For AI developers and engineers
The level of confidence in AI is very buoyant. However, focusing on getting business results is critical to short and long-term effectiveness. Every aspect of the AI journey – data capture, data management, model production, testing and deployment, should measure business value. Most AI developed still depend on a high percentage of human input. Focusing on higher AI capability with lower human input increase return and lower costs in the long term.
Trust and sharing data are also critical to success. The key is unlocking potential with confidence in the infrastructure.
Thank you, Infosys report.
Please note
I have no affiliation with the companies/technology/people mentioned. This analysis is 100% independent for the benefit of the data/business community. Please feel free to share this on your social network. Thank you.
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