Deep Dive: AI Tools for the Non-Technically Inclined Director

Summary

• This article explains three key AI technologies, with examples from construction, customer service, and local government.
• AI is a practical tool that performs tasks requiring human intelligence and is available to businesses without the need for knowledge of coding or complex algorithms.
• Understanding AI basics enables directors to ask informed questions and make strategic decisions, leveraging AI to innovate and compete.

“We are now solving problems with machine learning and artificial intelligence that were in the realm of science fiction for the last several decades.” - Jeff Bezos

Introduction

We need to think of Artificial Intelligence (AI) not as science fiction but as a tool we use every day. AI helps machines or software do tasks that usually need human intelligence. This includes learning from past actions, understanding spoken or written words, recognising patterns, and making decisions.

The goal of this article is to make AI less of a mystery. We want to show that understanding AI doesn't mean you have to know how to code or work with complex algorithms. Instead, it's about seeing AI's value to a business.

Knowing the basics of AI allows directors to ask smart questions, lead meaningful conversations, and make wise choices about using AI in their company's strategy. This knowledge is crucial in leveraging AI's power to innovate and stay ahead in today's competitive market.

Three Key AI Technologies Explained

AI is a broad field encompassing technologies that can transform how businesses operate and engage with their stakeholders, such as customers, suppliers, employees, and regulators. Understanding these key technologies is crucial to identifying opportunities for strategic implementation. Here's a simplified overview:

Machine Learning and Predictive Analytics: At the heart of many AI applications, machine learning enables computers to learn from data, improving their accuracy over time without being explicitly programmed. Predictive analytics uses this data to forecast future trends, helping businesses anticipate market changes or customer needs.

• Example - Construction:?Machine learning algorithms can significantly improve the tender process for large projects like skyscrapers, railway lines, stadiums, etc. By analysing data from previous successful and unsuccessful tenders, these algorithms can calculate the cost of new projects much quicker and with significantly increased accuracy. The increased speed and accuracy provide a significant advantage by allowing more competitive bids to reach the customer's evaluation team much earlier.

If your company submits a bid in 2 months and your competitors submit theirs 8-10 months later, how much would that improve your chances of winning the tender?

Natural Language Processing (NLP): NLP allows machines to understand and interpret human language. This technology powers chatbots and virtual assistants, enabling them to handle customer inquiries or support requests efficiently, often in a conversational manner.

• Example - Customer Service:?NLP enables machines to interpret human language, allowing for more natural technological interactions. Let's consider a word like "bank," which can mean the side of a river or a financial institution. NLP allows for understanding the difference based on context. If a customer asks, "What are the bank's hours?" a chatbot will understand they're referring to a financial institution. But if the question is "How can I find the bank of the river?" the chatbot interprets "bank" differently, demonstrating NLP's ability to grasp nuances in language.

Computer Vision: This AI technology enables machines to interpret and act upon visual data. Computer vision has diverse applications, from analysing images to identifying defects in manufacturing lines to powering security systems that recognise faces.

• Example - Local Government:?The author was involved in a project where a local government authority in Southeast Asia wanted to use computer vision for road maintenance. Cameras mounted on pushbikes will scan the streets for potholes. The computer vision system will identify and locate these potholes and assess their size. This data is then transferred to the in-house works management system to prioritise and schedule maintenance, ensuring the most critical repairs are addressed promptly.

Conclusion

In this article, we saw that Artificial Intelligence (AI) is not just future tech but a tool we use today to make businesses better. AI helps in many ways, like making operations more efficient, improving how we talk to customers, and keeping our infrastructure secure.

As board directors, your role in bringing AI into your company is crucial. With a basic understanding of AI, you can lead meaningful discussions, make intelligent decisions, and help your company stand out.

We encourage you to use AI and lead its adoption thoughtfully. As we progress, your leadership and ethical approach will be vital in maximising AI for your business and the wider community.

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We have developed our "Shaping Success with AI?" (SSAI?) framework to help Board Directors understand, introduce, and govern AI in their organisations. SSAI? aims to help Board Directors move from User or Learner to Trailblazer and lead profoundly impactful organisations.

If you're a Board Director introducing AI into your organisation, don't hesitate to get in touch with me for an exploratory discussion. You can reach me at [email protected] or, alternatively, you can book directly a 15-min confidential session at https://bit.ly/mbojilov-15min or by using the QR code below.