Your AI Cheat Sheet: How To Predict What's Next in an Unpredictable World
- Alex Burkart, President
- Mar 22
- 4 min read
Updated: Jun 17
When it comes to navigating AI, staying ahead is all about knowing what questions to ask.
For anyone drowning out there trying to keep up with what's coming next, keep reading. 👇
First, imagine you could teach a computer to understand endless mountains of data from every source imaginable.
↳ Image, text, audio, and video capture sensors
↳ Sonar, radar, infrared, lidar, GPS, and RFID sensors
↳ Ultrasonic, thermal, magnetic, and chemical sensors
↳ Biometric, optical, electromagnetic, and piezoelectric sensors
↳ Gas, radiation, weather, and environmental sensors
↳ DNA, biosensors, EEG, ECG, and medical sensors
↳ Strain, accelerometer, gyroscope, and mechanical sensors
↳ Quantum and advanced imaging sensors
↳ Edge computing, mesh network, and IoT sensors
Now imagine that same computer could interpret all of this data and talk back to you with the knowledge and expertise of every subject matter in existence.
Over time, it doesn't just talk back; it has enough data and training to perform tasks with precision light years beyond human capability.
That's AI in a nutshell.
What does this mean for predicting market behavior?
✅ Data Collection-Enabled Hardware Innovation
Now that we have technology that can make sense of mountains of data, the door to tap into data yet to be collected is insane. This means everything from building materials and construction to textiles, wearables, and implants. Ask yourself how a future hospital or retail store might be constructed. Or maybe you want your dog to live longer and are interested in the new chip that predicts and prevents disease.
Example: Purina VetChip
✅ AI-Enabled Hardware Innovation
Expect breakthroughs like medical imaging systems that provide the results without the need for radiologist techs. Or consider fully automated warehouses and shipping yards with self-driving cranes and forklifts that cripple the leverage of workers from ever going on strike.
Example: Self Driving Forklifts
✅ Task Assistance Innovation
Leveraging AI to predict bottlenecks and optimize resources might be obvious, but there’s a bigger opportunity. AI assistants can take over routine check-ins and FAQs and even act as mental health coaches for your team. By spotting patterns in communication and flagging burnout risks, AI will enable managers to keep teams engaged and performing at their peak. It’s not just about managing tasks; it's about elevating the human side of team performance.
Example: AI Business & Mental Health Coach
✅ Task Automation Innovation
Once proven accurate and safe, AI will fully own tasks from start to finish. It's not a matter of if; it's a matter of when. Will lawyers still hit their hourly quotas when legal research can be done in minutes? Or consider the environmental, financial, and production downtime savings from structural imaging systems that scan for wear and tear, utilizing infrared, ultrasonic, lidar, and vibration sensors to trigger the automatic ordering of replacement parts and schedule maintenance without human input?
✅ Increased Cybersecurity & Privacy Challenges
As AI scales, so does its dark mirror. The same tech that powers innovation is arming bad actors with tools we’ve never seen before. Security isn’t just about firewalls anymore; it's about fighting threats that think, learn, and mimic us.
✅ Trends For Human Capital
Take all of these examples, map their value chains, and then ask:
→ What jobs have repetitive workflows?
→ What jobs are rote-memorization heavy vs critical thinking driven?
→ What jobs require human fact-checking?
→ Where is human oversight legally or ethically required?
→ What value-added experiences require human interaction?
Understanding market behavior is one thing.
Keeping up with the firehose of AI tools? That’s a full-time job on its own.
But ignoring it isn't an option, not if you want to stay relevant.
The risks to your career or business aren't hypothetical. They're already here.
In Building a Second Brain, Tiago Forte introduces the idea of extended cognition, the concept that our brains treat tools as literal extensions of ourselves. When you pick up a rake, your brain instinctively accounts for the extended reach. Digital tools work the same way. With the right ones, your mind stretches further.
The key isn't learning every new tool. It’s knowing what problem you’re trying to solve and trusting that a tool exists (or soon will) to solve it.
→ What outcomes do you need?
→ What capabilities do you lack?
→ What tools close that gap?
As AI grows around every niche across industries, functions, and data types, your job isn’t to master them all. It’s to stay sharp enough to know which tools are worth your time and which ones to ignore completely.
If you're looking to stay ahead without burning out, check out the resources below.
