Unlocking the True Potential of AI: Introducing Engineered Intelligence
As we stand on the cusp of a potential fourth AI winter, doubts are beginning to arise about whether AI will deliver enough tangible value to justify its cost. Recent reports from Goldman Sachs and other research institutes have only added to this skepticism. However, there may still be a way to prevent this looming AI winter, and the answer has been right in front of us all along.
The Missing Piece: Applied Artificial Intelligence
In most scientific disciplines, breakthroughs are made in laboratories and then handed off to engineers who transform these discoveries into real-world applications. For example, when chemical researchers uncover a new way to form an adhesive bond, chemical engineers take over to engineer practical solutions. Similarly, mechanical physicists collaborate with mechanical engineers to engineer solutions based on breakthroughs in their field.
Yet, when it comes to AI, there is no distinct discipline for applied artificial intelligence. Instead, organizations often hire data scientists with PhDs in AI research, hoping they can engineer real-world solutions. The result? A staggering 87% of AI projects fail.
Introducing Engineered Intelligence
Engineered intelligence, or intelligence engineering, is an emerging discipline that focuses on the real-world application of AI research through an engineering lens. It bridges the gap between scientific breakthroughs and practical value creation by combining expertise from various domains. By leveraging breakthroughs in science and engineering, domain experts, scientists, and engineers can create intelligent solutions without needing to become data scientists themselves.
Leading industrial organizations have already started reestablishing research-to-engineering pipelines, forging partnerships with academia and technology vendors, and creating the necessary ecosystem for AI research to be handed off to intelligence engineers, just as chemical research is shared with chemical engineers.
The Result: Breakthrough Applications and Tangible Value
By embracing intelligence engineering, organizations can unlock breakthrough applications in tangible use cases that create real value and make it into production. These applications are often ones that data scientists or technology vendors would not have discovered based on data alone. The marriage of scientific breakthroughs and engineering expertise paves the way for innovative solutions that can transform industries and drive economic growth.
Introducing Intelligence Engineering to Your Organization
To introduce intelligence engineering to your organization, you need to focus on expertise, which is the heart of this discipline. Expertise is expressed as skills and is acquired through practical experience. Here are five practical steps to follow:
1. Create a heatmap of expertise across your existing processes.
2. Assess the value and scarcity of different expertise areas.
3. Identify the top five most valuable and scarce expertise areas in your organization.
4. Analyze these areas for return on investment, feasibility, cost, and timeline to engineer intelligent solutions.
5. Choose a subset of value cases and invest in their execution.
Engineering a New Wave of Value with AI
Once intelligence engineering is embedded in your organization, you can leverage this capability to extend beyond existing expertise and explore new opportunities for engineering safe and practical value. This shift can lead to the creation of a new class of jobs, the realization of the economic and societal potential of AI, and a new wave of value creation.
In conclusion, by embracing intelligence engineering and combining scientific breakthroughs with practical expertise, organizations can unlock the true potential of AI. It’s time to bridge the gap between research and application, transforming the AI landscape and creating a future where AI delivers tangible value for all.