5 Ways to Use AI You May Have Never Even Considered

February 19, 2024

AI has already been applied to an array of business and personal uses. Here are some that may come as a surprise to you. (AI for pest control, anyone?)

It’s widely believed that AI’s potential has only reached the Commodore 64 stage. In other words, the best is yet to come.

As the technology gains momentum, innovation is flourishing, with new applications seemingly limited to only its users’ imagination. Consider the following five examples that show how AI will continue to surprise and transform both personal and business activities.

1. Personalized teaching

AI can augment and accelerate the way individuals acquire knowledge and skills by fine-tuning educational experiences to the specific needs, learning styles, and multiple intelligences of each learner, says Paul McDonagh-Smith, senior lecturer of IT at MIT’s Sloan School of Management, via an email interview. “AI can employ advanced algorithms to customize educational content and feedback based on a student’s unique profile and progress, leading to better educational outcomes,” he explains. “This innovative application of AI has the potential to revolutionize education by making it more tailored, engaging, and accessible to learners of all backgrounds and abilities.”

2. Idea generation

AI systems like GPT-3 can generate novel concepts and suggestions by analyzing large amounts of text data. “This can help spark new ideas for products, services, and business models that humans may not have thought of on their own,” says Scott Lard, general manager and partner at IS&T, an information systems technology search and contingency staffing firm, via email.

What makes this approach useful is that AI systems can consider far more possibilities and variations than a single human mind, Lard explains. “By analyzing thousands of existing ideas, it can provide fresh perspectives and out-of-the-box thinking that helps organizations innovate.”

Lard suggests the best way to get started with AI-enabled idea generation is to simply ask an AI model open-ended questions about potential new ideas and concepts within a specific industry or focus area. Give the AI system as much relevant context as possible to narrow the results, he advises. Then review the generated ideas to see which offer the most potential to explore further. “You can then iterate the process by refining your questions and context to produce even better results over time.”

3. Mental health support

By providing a continuous and non-judgmental presence, AI can help address the escalating demand for mental health support, says Siraj M A, director of data and analytics at project engineering firm Experion Technologies, in an email interview.

Virtual companions, powered by AI, can deliver personalized interventions tailored to individual needs and preferences, M A explains. “These AI entities go beyond mere assistance; they can collect and analyze data over time, unraveling patterns crucial for a deeper comprehension of … mental health.”

When used appropriately, AI-driven virtual therapists could surmount geographical constraints, democratizing mental health care globally, M A says. “Such solutions could ensure timely support, especially for those facing barriers due to location or a limited mental health infrastructure.”

M A recommends that new adopters should start by bringing together a team of mental health and AI experts to review potential opportunities. “The team should focus on identifying the right use cases in their industry, and then identify solutions that could help with early intervention, therapy support, or diagnostic assistance,” he advises. “These objectives should then be evaluated alongside the data, technology and infrastructure available to come up with a list of prioritized use cases that can be pursued.”

4. Staff hiring

With the assistance of AI-powered team recommendation engines we can help our hiring managers pinpoint the best candidates for a specific job, says Juan Nassiff, technical manager and solutions architect at custom software development firm BairesDev, via email.

BairesDev gets more than a million job applications every year, which is virtually impossible to sort through manually, Nassiff says via email. “We leverage complex machine-learning algorithms to match talent in our database with unique project requirements that we have a need for,” he states. “Our method goes beyond the traditional use of AI in customer service or data analysis, focusing on optimizing team assembly for software development projects.”

Nassiff says the approach is “incredibly useful,” since it ensures an equitable and skill-focused hiring process, eliminating the biases that can occur in traditional recruitment practices. “By focusing solely on skills, professional experience per skill, and project requirements, our Team Recommendation Engine enables the assembly of highly effective teams that are tailored to specific client needs,” he explains. “This not only improves project outcomes, but also significantly reduces the time and resources typically spent on recruiting and team formation.”

5. Pest control

By analyzing multiple factors, such as weather and geography, AI can help exterminators build and optimize pest control measures. “This approach is particularly useful because it allows for proactive pest management, reducing the reliance on reactive and potentially harmful chemical interventions,” says Rubens Tavares Basso, CTO at pest control software provider Field Routes, via email.

Basso advises potential adopters to consider data privacy and security concerns before implementing AI pest control technology. “Additionally, businesses should be mindful of potential biases in the AI algorithms and regularly update their system to adapt to changing environmental conditions,” he says. “AI in pest control software provides a forward-thinking, eco-friendly solution to managing pest issues, promoting sustainable and effective practices in agriculture and other industries.”

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