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Taking AI to the next level
Harnessing the full potential and value of AI while managing its unique risks
Artificial intelligence (AI) has become a clear and undeniable force for business disruption and transformation. It is delivering significant business benefits today—and its potential to shape the future is even greater. In fact, the main challenge now is how to scale up AI-led innovations to deliver the greatest impact as efficiently and effectively as possible while at the same time managing AI’s unique risks.
Explore content
- AI demystified
- Predict, prioritize, & capture
- Architectural capabilities
- Workforce
- Tackle the challenges of AI
Although AI value and AI risk are often viewed as separate and distinct, these four key questions can help you address both factors simultaneously:
- Value: How do you predict, prioritize, and capture the value of AI for your business?
- Architecture: What architectural capabilities are needed to scale AI?
- Workforce: How will AI affect your workforce?
- Governance: How do you tackle the challenges of AI responsibility, ethics, and governance to harness AI’s full potential and value?
Let’s take a look at these four questions and the overall AI journey.
Artificial intelligence demystified
Theorists have been arguing for decades about what constitutes true “intelligence”—both in machines and in people—and that debate might never end. However, in practical terms, a good working definition of AI is:
Computer systems able to perform tasks normally requiring human intelligence.
Key things to know about AI:
- AI systems learn. Unlike traditional computer systems explicitly programmed to follow sets of rules and produce deterministic outcomes, AI systems get smarter over time, sometimes on their own.
- AI’s “intelligence” is based on underlying capabilities similar to those of human intelligence.The core capabilities of AI are similar to those of human intelligence, such as clustering (pattern recognition), categorization, anomaly detection, and regression and prediction.
- There are many ways to achieve AI. AI systems use a variety of methods and algorithms, including symbolic reasoning, Bayesian inference, connectionist AI (neural networks), genetic algorithms that emulate evolution, and learning by analogy.
Taking AI to the next level
A sampling of AI capabilities
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How do you predict, prioritize, and capture the value of AI?
Although AI’s overall ability to create business value is now widely accepted, the specific impacts AI is likely to have are not as well understood and vary by company and industry. Here’s a structured way to think about existing and future ways that AI can create business value. It's made up of five fundamental levers:
The five levers for AI value
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What architectural capabilities are needed to scale AI?
AI requires the right supporting architecture and infrastructure. Without that solid foundation, your AI solutions will be severely limited, prohibitively expensive, or just won’t work. Fundamental elements of an AI-enabling technology architecture:
How will AI affect your workforce?
Many of AI’s most compelling use cases involve machines and people working together as a team, with AI augmenting humans—not replacing them. AI workforce implications can be divided into three broad categories:
How do you tackle the challenges of AI responsibility, ethics, and governance?
Because AI often learns and behaves like a human, it presents many of the same kinds of risks that a company faces in its human workforce. As such, without effective safeguards, AI might act in ways that are unpredictable or have unintended consequences.
Achieving trustworthy AI that is responsible and ethical requires effective governance in every phase of the AI life cycle. Waiting until after problems arise can have significant legal, regulatory, and financial repercussions. It can also cause significant reputation damage and embarrassment for a company and its leaders.
Six key attributes of trustworthy AI:
The AI journey: How do we get from here to there?
Whether you are starting with a clean slate and approaching AI from the top down or starting with your existing AI initiatives and building up from there, all four dimensions must be addressed. Crafting and executing an AI strategy that considers these four dimensions will help your company scale up quickly to capture the full benefits of AI without getting bitten by AI’s unique risks.
Before you know it, you might find your company has become a next gen AI company.
Endnotes
1 European Union General Data Protection Regulation
Get in touch
Beena Ammanath
Global Deloitte AI Institute Leader | Trustworthy AI Leader
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