Conquering the Fear of Embracing AI

There is more transparency than ever into how AI tools work and how they benefit organizations

Michael Amori, CEO and co-founder, Virtualitics

August 14, 2024

3 Min Read
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Despite the benefits of AI, some business leaders are still hesitant to add it to their technology stacks. There is still the misconception that AI, whether it's used in robotics on the factory floor or machine learning algorithms for data analysis, is too complex and unpredictable to unleash. 

But the reality is that most AI tools aren’t as opaque as they once were and there is now more transparency than ever into how they work and how they benefit all organizations.

Understanding the True Potential of AI

There has been a long-held fear that AI would replace jobs done by humans or introduce too much risk by operating independently of human intervention. But innovations in AI have focused more on technology governance and responsible practices and investments in employee reskilling and upskilling programs have paved the way for more trust and confidence in these technologies. 

Of course, success is best achieved when humans and machines work in tandem. Explainable AI has been a large part of what makes this collaboration possible. Explainable AI uses natural language processing to provide AI users with context-aware explanations featuring simple language and relevant visualizations to build confidence in the insight presented.

Explainable AI is crucial to faster decision-making since it enables even non-technical audiences to engage with and trust AI technologies. By breaking down complex models into understandable terms, the black box around AI is lifted and anyone can feel empowered to use AI accurately and in alignment with business goals and values.

Related:Unlocking AI’s Potential for Nonprofits Requires Data Transformation First

So how can AI be introduced in a business? Below are four key applications:

1. Data Analysis

Innovative analytics platforms leverage AI to automatically find insights for business analysts and suggest, in plain language, what to do next to explore the data more in-depth. These technologies also deliver more accurate reports since some models can highlight errors or even predict potential issues before they happen. 

2. Understanding Customers

AI powers the chatbots and virtual assistants that help answer routine questions, guide customers through their buying journey and escalate complex customer service issues to the right departments. This not only boosts customer satisfaction but also frees up human customer service agents to focus on critical queries. AI also has the power to find communities and trends in your customer base, identifying groups that will be likely to respond well to marketing opportunities. 

3. Resource Optimization

Related:Generative AI Explosion Requires New Compute Approaches

Integrated resource optimization is a data-driven approach that provides a big-picture view of maintenance operations. Integrated resource optimization leverages AI to do deep analysis on complex, interrelated data sets, while also automatically surfacing the most significant insight within every analysis. This allows maintainers to spend the right time and resources on truly strategic preventative actions, rather than reactively fixing broken systems.

4. Predictive Analytics

One of AI’s greatest benefits is that it gives businesses the ability to make predictions. By ingesting and analyzing historical data to identify patterns and trends, AI does the legwork that then empowers businesses to make proactive decisions and anticipate future challenges. This foresight is extremely useful for strategic planning and risk mitigation.

An AI Mindset is a Collaborative One

AI has a transformative power that vastly improves decisions throughout a business. Not only does it do the routine, heavy-lift jobs that can bog people down in the decision-making process, but it can also automatically surface insights and fuel AI-driven applications that present valuable information in explainable, easy-to-understand terms that empower non-technical or data-savvy users to make smarter choices. 

When AI is viewed not as a threat, but rather a collaborative partner, that’s when organizations will truly succeed now and in the future. 

About the Author

Michael Amori

CEO and co-founder, Virtualitics, Virtualitics

Michael Amori is the CEO and co-founder of Virtualitics. Michael is a data scientist and entrepreneur with a background in finance and physics. He co-authored many of the patents underpinning the Virtualitics AI platform. He believes that AI applied to data analytics can help solve some of the world’s toughest challenges.

Before co-founding Virtualitics, he was a managing director at Deutsche Bank, where he started and headed a data-driven trading desk in London, New York and India focused on the insurance and pensions markets. He managed a large group of data scientists, designed the group’s predictive modeling and risk management systems and started and was technical advisor to the bank’s first insurance-linked fund. He was previously an interest rates derivatives trader at various large banks and graduated from the Goldman Sachs analyst program.

Michael was also a researcher in nanotechnology at Caltech, where he contributed to two papers and obtained one patent. The patent is related to a quantitative method for the determination of target molecules in the context of nanotechnology devices applied to medical research.

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