Risky Business: The Rise of Cognitive Technologies

Risk management, a field long dominated by human intuition and experience, is undergoing a transformation. Recent advancements in cognitive technologies, artificial intelligence (AI), and data analytics have revolutionized how risks are detected, predicted, and prevented, particularly in high-risk scenarios. One of the most intriguing innovations in this area is the rise of autonomic computing, which leverages both automation and cognitive technologies. Such systems don’t just manage risks; they can defend against and even heal from them.

What’s Driving This Evolution in Risk Management?

1. Massive Growth in Data Availability: Organizations are awash in data like never before. From transaction records to social media engagements, the influx of data is immense.
2. Emergence of Advanced AI-based Algorithms: These algorithms can parse vast datasets, understand patterns, and make predictions or suggestions based on that understanding.
3. Growing Data Science Talent Pool: As interest in AI and machine learning has surged, there’s been a parallel rise in professionals skilled in these areas.
4. Adoption of Behavioral Analytics: This approach involves tracking, collecting, and assessing user data to understand the interactions between different elements. It’s particularly useful for understanding nuanced risks.

Spotting the Opportunities

1. Identifying Ideal Use Cases: Cognitive technologies shine brightest in situations where the risk area is crucial, large datasets are at hand, and traditional methods fall short.
2. Harnessing the Power of Visualization: By presenting data in intuitive, visual formats, organizations can facilitate more informed and rational decision-making.
3. Upskilling the Workforce: As machines become smarter, it’s imperative that the human workforce evolves alongside. Training employees to use these advanced tools can maximize the insights drawn from data.

Navigating the Challenges

While the potential is vast, so are the challenges:

1. Implementation Hurdles: Not every organization has the infrastructure or expertise to deploy complex cognitive tools seamlessly.
2. Overhyped Technologies: Not all that glitters is gold. Some technologies, despite their promise, may not deliver as expected.
3. Trust Issues with AI: As machines take on more decision-making roles, ensuring their reliability and transparency becomes paramount.
4. Data Sourcing Challenges: The right data is crucial. Inaccurate or incomplete data can lead to flawed insights.
5. Human Resistance: Many fear what they don’t understand, and a shift towards automated decision-making can lead to pushback.
6. Unintended Outcomes: Even the smartest systems can make errors. The consequences of AI-driven decisions gone awry can be significant.

Real-world Examples of Cognitive Technologies in Action

1. Warwick Analytics: This company’s early warning and prevention system foresees potential maintenance needs in products, such as vehicles or aircraft. By identifying the root causes of failures, corrective measures like remanufacturing or redesign can be undertaken. The resulting economic benefits include more efficient production lines, reduced energy consumption, and prolonged product life cycles.
2. Deep Knowledge Ventures: In a bold move, this Hong Kong-based venture capital firm added an AI, “VITAL,” to its Board of Directors. VITAL makes investment decisions by thoroughly analyzing data on prospective companies, showcasing the potential of AI in decision-making roles.
3. Nexgate: Specializing in Deep Social Linguistic Analysis and natural language processing, Nexgate offers tools for social media risk management. From detecting fraudulent accounts to ensuring compliance with industry standards, Nexgate illustrates the depth of AI’s capabilities in risk management.

The landscape of risk management is rapidly changing. For forward-thinking organizations and professionals, embracing these changes doesn’t just offer a competitive edge—it paves the way for a more secure and insightful future. The blend of human intuition with machine intelligence promises a synergy that can redefine the boundaries of what’s possible in risk management.

Managing your artificial intelligence governance can be difficult if the right software isn’t in place to manage your risk. Expose your risk with emerging cognitive technologies by using Connected Risk‘s AI Governance Management solution, the only risk management focused solution designed specifically to model your risk effectively and efficiently.