Artificial Intelligence (AI)
As AI capabilities rapidly evolve it’s vital to scale from experimentation to implementation. The businesses successfully achieving AI at scale are disproportionately financial outperformers. How do they accomplish this? By confronting data issues and bridging the AI skills gap. Find out how your business can do the same and become an AI innovator.
Increasingly pervasive in our lives, artificial intelligence, and machine learning (AI/ML) promise to launch a fourth industrial revolution on par with mechanization, electricity and computer technologies. Virtual assistants, autonomous driving vehicles and robot deliveries are early practical examples of how AI/ML is being put to use.
Foundational elements of such an outlook might include:
- Ethical use of technology in which the mission of serving people is never lost.
- Running pilot programs to become adept at the use of AI.
- The reimagining of organizational models, allowing departments to manage AI/ML.
- A focus on data, the only foundation from which AI can produce meaningful results.
- A rethinking of work where human decision-making is aided by the insight offered my machines.