Sign up to save your podcasts
Or
Share Why Most AI Tools Don’t Actually Help Businesses
Share to email
Share to Facebook
Share to X
Share to email
Share to Facebook
Share to X
Or
Why Most AI Tools Don’t Actually Help Businesses
AI adoption isn’t failing because the technology doesn’t work—it’s failing because expectations, fear, and poor implementation get in the way.
In this episode, AJ Malik, founder and CEO of PsychoMind, shares a grounded perspective on how businesses can actually succeed with AI. With roots in AI going back to a 1989 expert system project at IIT, AJ brings decades of experience from companies like Google, Cisco, and Motorola, along with years building AI platforms for real-world business use.
AJ explains why many so-called AI tools today fall short, describing them as thin wrappers around ChatGPT that lack persistence, context, and integration. Instead of chasing point solutions, he argues that organizations need centralized AI platforms that work with their data, systems, and workflows—securely and predictably.
The conversation breaks down the three biggest obstacles companies face when adopting AI: expecting unrealistic “super intelligence,” struggling to give up control over decisions, and fearing failure due to past hype cycles like blockchain or 3D TV. AJ explains how starting with small proof-of-concept projects can remove risk and build confidence.
AJ also reframes AI’s role, comparing it to a shift from search to answers—from a sixth sense to a seventh sense. Rather than replacing humans, AI handles most of the heavy lifting while people remain responsible for the final 15%: judgment, ethics, and creativity. The result is not automation for its own sake, but better decision-making at scale.
View all episodes
By Mike MahonyAI adoption isn’t failing because the technology doesn’t work—it’s failing because expectations, fear, and poor implementation get in the way.
In this episode, AJ Malik, founder and CEO of PsychoMind, shares a grounded perspective on how businesses can actually succeed with AI. With roots in AI going back to a 1989 expert system project at IIT, AJ brings decades of experience from companies like Google, Cisco, and Motorola, along with years building AI platforms for real-world business use.
AJ explains why many so-called AI tools today fall short, describing them as thin wrappers around ChatGPT that lack persistence, context, and integration. Instead of chasing point solutions, he argues that organizations need centralized AI platforms that work with their data, systems, and workflows—securely and predictably.
The conversation breaks down the three biggest obstacles companies face when adopting AI: expecting unrealistic “super intelligence,” struggling to give up control over decisions, and fearing failure due to past hype cycles like blockchain or 3D TV. AJ explains how starting with small proof-of-concept projects can remove risk and build confidence.
AJ also reframes AI’s role, comparing it to a shift from search to answers—from a sixth sense to a seventh sense. Rather than replacing humans, AI handles most of the heavy lifting while people remain responsible for the final 15%: judgment, ethics, and creativity. The result is not automation for its own sake, but better decision-making at scale.