A few years ago, if artificial intelligence came up in a business meeting, the conversation would quickly turn technical. People would talk about algorithms, machine learning and data scientists.
That has changed.
Today, AI is appearing in ordinary workplaces. A marketing manager uses it to develop campaign ideas. Someone in finance uses it to analyse information. A manager uses it to prepare a report or explore a business problem. An executive uses it to make sense of a large amount of information before a meeting.
The interesting question is no longer whether businesses will use AI. Many already are.
The harder question is whether managers know how to use it well.
Being an AI-ready manager doesn’t mean becoming a programmer. It means knowing enough about AI to recognise where it can help, understanding its limitations, and making sensible decisions about how to introduce it into an organisation.
Here are ten things worth learning.
1. Start with the basics of AI
You don’t need to understand the mathematics behind an AI model. But if you’re going to make decisions about AI, you should have a basic understanding of what you’re dealing with.
What is machine learning? What is natural language processing? What is automation? How do these technologies relate to the AI applications businesses use today?
A manager doesn’t need to become an AI specialist, but understanding the principles makes it easier to have sensible conversations with technology teams and evaluate how AI might apply to a real business problem.
A programme to consider: RKC’s MSc Managing AI in Business includes Principles of AI, which explores the AI ecosystem, machine learning, neural networks, emerging AI architectures and the development of AI concepts.
2. Don’t look for places to use AI. Look for problems to solve.
Businesses are tempted to adopt new technology because everyone else seems to be doing it.
AI is particularly prone to this. If a competitor is using it, you should use it too.
Not necessarily.
A better place to start is with a problem. Perhaps a business needs to use its data better. Perhaps an organisation wants to improve a particular process. Perhaps there is an opportunity to use AI in a marketing activity or to support decision-making.
The question isn’t simply, “How can we use AI?”
It’s “Is there a business problem that AI could help us address?”
That distinction matters. Good management has always been about matching resources and technology to real business needs. AI doesn’t change that.
A programme to consider: The MBA Artificial Intelligence at RKC includes an Artificial Intelligence module that examines how AI concepts, including machine learning, can be applied to real-life business problems and applications.
3. Learn how to work effectively with AI
Many people have tried an AI tool once, asked it a question, received a mediocre answer, and decided the technology wasn’t very useful.
Often, the problem is how you ask the question.
Working effectively with generative AI takes practice. Providing the system with context, explaining what you are trying to achieve, and refining the result can make a considerable difference.
It is also important to know what AI can and cannot do. An AI-generated answer is not automatically reliable simply because it is well written.
This is becoming a practical professional skill: knowing how to use AI tools, evaluate their outputs, and incorporate them into your work while retaining human judgement.
A programme to consider: RKC’s MSc Strategic Leadership with AI includes AI for Business and Professional Practice, covering AI literacy, prompt design, AI-assisted research, source checking, reliability and bias, and AI-supported decision-making with human judgement.
4. Don’t believe everything AI tells you
This may be the most important lesson of all.
AI responses can sound extremely confident—even when they are wrong.
That matters in a business context. If an AI system produces inaccurate information and nobody checks it, the problem can quickly become a business issue.
Managers therefore need to develop the habit of questioning AI-generated information, particularly when it supports important decisions.
This doesn’t mean distrusting AI. It means understanding its limitations.
The ability to check sources, recognise unreliable information, and distinguish between useful assistance and an answer that needs further investigation is increasingly important.
A programme to consider: The MSc Digital Marketing with AI includes AI for Business and Professional Practice, covering source checking, hallucinations, reliability, and bias. These are useful concepts for anyone who expects to use AI in their professional work, not only those working in marketing.
5. Understand the ethical side of AI
Sometimes “Can we do this?” isn’t the same as “Should we do this?”
AI can influence decisions affecting employees, customers and other stakeholders. That raises questions about bias, trust, transparency and accountability.
Consider an organisation using AI to support workplace decision-making. How should the results be evaluated? How much trust should be placed in the system? Where does human responsibility begin and end?
These are management questions as much as they are technology questions.
An AI-ready manager needs to be comfortable thinking about AI’s wider implications, rather than focusing only on what the technology can do.
A programme to consider: RKC’s MSc Managing AI in Business includes AI in Practice, which examines regulatory frameworks and ethical considerations, and Principles of AI, which explores bias and trust in AI systems. Its Sustainable Business and Responsible Technology module also examines ethical leadership and responsible technology adoption.
6. Understand how AI fits into business transformation
Introducing AI into an organisation isn’t simply about buying a new tool.
It can change processes, responsibilities and the way people work. It can also meet resistance, particularly when employees aren’t sure why the change is happening or how it will affect them.
This is where the manager’s role becomes particularly important.
Someone has to look beyond the technology and consider how AI fits into the organisation as a whole.
What needs to change? How will people respond? How should the organisation approach adoption? What does successful integration look like?
A programme to consider: RKC’s MSc Managing AI in Business includes AI and Business Transformation, which covers AI adoption, digital mindset, leadership, organisational culture and managing resistance to AI integration.
7. Pay attention to how AI is changing people’s work
The question “Will AI take my job?” attracts a lot of attention.
For a manager, a more useful question is:
Which parts of people’s work are likely to change?
AI is already reshaping how employees interact with information and technology. Some activities may be automated, while others may require new skills or different responsibilities.
This poses a management challenge. Employees need to understand how AI affects their work, and managers need to consider employee well-being and the human side of AI adoption.
The future of work is unlikely to be simply humans versus machines. In many workplaces, people will work alongside increasingly capable technologies.
A programme to consider: RKC’s MSc Managing AI in Business addresses the role of AI in workplace decision-making and employee wellbeing in AI in Practice, while AI and Business Transformation examines leadership, culture and resistance to AI integration.
8. Learn to make better decisions with data and AI
AI and data are closely connected.
For managers, the challenge isn’t necessarily to become a data scientist. It is to understand how data and AI can support better business decisions.
That means becoming familiar with concepts such as business intelligence, data modelling, predictive analytics, and using data to identify patterns and support decision-making.
The more data-driven organisations become, the more important it is for managers to understand how those insights are produced and used.
A programme to consider: RKC’s MSc Business Analytics and Artificial Intelligence is particularly relevant here. Its modules include Data-Powered Decision Making, covering big data management, business intelligence, data modelling, and industry-specific AI applications, and Leading with Analytics and AI, which covers predictive analytics and AI-supported strategic decision-making.
9. Don’t confuse using AI with getting value from AI
Organisations can fall into a simple trap: confusing using AI with getting value from AI.
Having employees experiment with an AI tool doesn’t necessarily mean the organisation is benefiting.
A better question is: what has changed?
Has the organisation improved its decision-making? Has AI helped address a real business challenge? Has it contributed to a more effective process? Has the organisation successfully integrated it?
These questions bring us back to management.
Technology provides possibilities. Managers still have to decide how those possibilities fit into the organisation.
A programme to consider: RKC’s MSc Business Analytics and Artificial Intelligence includes the Future Leaders’ Challenge, which focuses on real-world business challenges, strategic thinking, innovation and digital transformation planning. Its Impact Project gives students the opportunity to apply their learning to a real-world business challenge.
10. Accept that you’ll never be “finished” learning about AI
Perhaps the most frustrating—and exciting—thing about AI is that it keeps evolving.
A tool you learn to use today may look very different a year from now. New applications will emerge, businesses will discover new uses for AI, and our understanding of its implications will continue to develop.
There won’t be a point at which a manager can say, “I’ve completed my AI training. That’s done.”
Continuous learning is becoming part of the job.
For some professionals, that may mean keeping up with developments through reading and experimentation. For others, postgraduate study can provide a more structured way to deepen their knowledge while connecting AI to their particular area of professional interest.
RKC now offers several programmes that take this approach from different angles. The MSc Managing AI in Business focuses specifically on AI, business transformation and responsible technology. The MSc Business Analytics and Artificial Intelligence combines AI with data and decision-making. The MBA Artificial Intelligence approaches AI from a broader management perspective. There are also specialist programmes, including the MSc Strategic Leadership with AI, MSc Digital Marketing with AI, MSc People Management with AI and MSc Finance with AI.
The right choice depends largely on where you are in your career and how you expect AI to affect your specific area of work.
The AI-ready manager
People often think becoming “AI-ready” means knowing how to use the latest AI tools.
I don’t think it’s quite that simple.
An AI-ready manager can look at a new technology and ask sensible questions.
What problem does this solve? How could it affect our organisation? What happens to our people? How reliable are the results? What are the ethical implications? And ultimately, will this make the business better?
Those questions require something AI can’t provide on its own: judgement.
That may be one of the biggest lessons of the AI revolution. The more capable the technology becomes, the more important good leadership may be.
Business leaders don’t need to compete with AI. They need to understand it well enough to make the most of it—while knowing when to step in and say, “Let’s stop and think about this.” In my view, that is what being an AI-ready manager really means.