Ai Primers: Moving Forward with Ai
Overcoming Hurdles, Gaining Competitive Edge
With the launch of ChatGPT, firms find themselves having to respond to rating agencies, investors and employees about their artificial intelligence (AI) strategy. Given the enormous investments going into it, AI continues to develop at a break-neck pace. Many firms have scrambled to get started simply for the sake of not falling behind. But the distance from use cases to scaling to delivering tangible results is not a short one. From my conversations with executives and experts, many agree on these key hurdles to overcome.
Knowledge/Communication Gaps
Clear Business Purpose
Data Challenges
AI Risks and Governance
Human Factors: Fear, Trust, Workforce Impact
AI & the Workforce: Strategic Implications
AI is a leadership challenge. As organizations rush to adopt AI, the hardest work isn’t about tech — it’s about shifting mindsets, reshaping workforce, and building trust.
This AI primer article discusses useful concepts and frameworks to help leaders at all levels approach AI adoption with clarity and purpose.
Data and AI for Non-Tech
Data is the lifeblood of AI/ML - but what exactly? This primer helps non-tech stakeholders digest the complexities of data in the context of AI adoption, covering the key data concepts most relevant to AI/ML applications.
Speak the AI Language
How familiar are you with key concepts and terminology of artificial intelligence (AI) technologies? Read on and find out.
Moving Forward with AI
With ChatGPT's launch, firms are now pressing to move forward with AI technology. The distance from use cases to scaling to delivering tangible results is not a short one though. Key hurdles include knowledge gap, strategy alignment, data challenges, AI risks and governance, and workforce impact. How to overcome these hurdles?