In McKinsey’s 2025 State of AI survey, 88% of organisations reported using AI in at least one business function — up from 78% a year earlier. For anyone weighing a one-year MBA, that number signals a real shift: AI has moved out of the technology department and into everyday business decisions. Marketing teams now use it to interpret customer data, finance teams to flag anomalies and risks, and strategy teams to synthesise research faster than before.
That shift changes what employers expect from managers. A modern MBA graduate is judged less on functional knowledge alone and more on whether they can work sensibly alongside AI and data. Encouragingly, managers do not need to become data scientists to do this. What they need is AI fluency — the judgement to know where AI adds value, how to read its output, and when human decision-making should take over.
This article looks at how AI is being applied across business functions, why that matters for one-year MBA and PGPM aspirants, and the practical skills worth building before you graduate.
AI Is Reshaping the Manager’s Role, Not Replacing It
The clearest change is in how managers spend their time. Rather than doing routine analysis by hand, they increasingly direct AI tools to draft, summarise, forecast, and surface patterns — then apply business judgement to the results. Common uses include data analysis, market research, forecasting, content and communication, process automation, customer insights, decision support and scenario planning.
Here it helps to separate two ideas. Technical AI expertise is the ability to build and train models — the domain of data scientists and engineers. AI fluency is the ability to use AI thoughtfully within a business context. Most managers need the second, not the first.
What is AI fluency for managers? AI fluency is the ability to identify where AI can help solve a business problem, interpret AI-generated output critically, and decide when human judgement should override it. It combines basic data literacy with domain knowledge and sound commercial reasoning.
This matters because the fastest-growing skills reflect it. The World Economic Forum’s Future of Jobs Report 2025 found that AI and big data top the list of fastest-growing skills, with 90% of surveyed employers expecting demand to rise by 2030 — while analytical thinking remains the single most sought-after core skill.
How AI Is Being Used Across Key Business Functions
AI is best understood as a business capability rather than a single technology. Its applications look different in each function, but the manager’s job stays consistent: frame the problem, interpret the output, and own the decision. The table below shows examples of where AI is increasingly being explored across functions.
| Business Function | Examples of AI Applications | What Managers Need to Understand |
|---|---|---|
| Marketing | Customer segmentation, campaign optimisation, content analysis, predictive insights | Customer behaviour, data interpretation and responsible AI use |
| Finance | Forecasting, anomaly detection, financial analysis, reporting | Financial judgement, data quality and risk |
| Consulting & Strategy | Market research, scenario analysis, industry research, synthesis | Problem framing, critical thinking and strategic judgement |
| Operations | Demand forecasting, process optimisation, automation | Process design, efficiency and implementation |
| Human Resources | Talent analytics, recruitment support, employee insights | Bias, privacy, people management and decision-making |
| Sales | Lead scoring, customer insights, sales forecasting | Relationship management, data interpretation and commercial judgement |
| Product Management | User research, product analytics, experimentation, prioritisation | Customer needs, business strategy and product decisions |
| Supply Chain | Demand planning, inventory optimisation, logistics analysis | Operational decision-making and data-driven planning |
A caveat matters here. Not all organisations use these applications at the same scale — McKinsey’s 2025 data shows that while adoption is broad, most companies are still early in scaling AI beyond isolated pilots. The examples above show what is possible, not what every employer has already implemented.
Why AI Fluency Matters for One-Year MBA Graduates
A one-year MBA is an accelerated management-learning environment, often designed for professionals who already have work experience. That makes it a practical setting to combine business fundamentals with AI awareness rather than treating the two separately.
The value lies in integration. A graduate who understands finance and can also interpret an AI-generated forecast is more useful than one who understands only one of the two. The same applies across marketing, operations and strategy. What employers reward is the combination: business fundamentals, functional expertise, data literacy, AI awareness, strategic thinking, communication, leadership and problem-solving.
This does not mean one-year MBA graduates are inherently better equipped than two-year MBA graduates — program quality and individual effort matter far more than format. But for experienced professionals with limited time, a shorter, intensive program can be an efficient way to build cross-functional capability while adapting to an AI-enabled workplace.
The AI Skills MBA Aspirants Should Start Building
You do not need to code to be AI-ready. The more useful skills sit at the intersection of business and technology.
What AI skills should MBA graduates develop? MBA graduates should build AI and data literacy, effective AI-assisted working, business problem framing, critical thinking, responsible AI awareness, and the ability to collaborate with technical teams.
In practice, these break down as follows:
- AI and data literacy — understanding basic AI concepts, interpreting data, and recognising the limits of AI-generated output.
- Prompting and AI-assisted work — using generative AI tools for research, analysis, ideation and summarisation, while validating what they produce.
- Business problem framing — deciding whether AI genuinely solves a problem, rather than using it because it is available.
- Critical thinking — questioning assumptions, spotting errors, and checking sources against reliable references.
- Responsible AI awareness — understanding data privacy, bias, hallucinations, intellectual property, security and the need for human oversight.
- Cross-functional collaboration — translating business requirements into practical work with data scientists, analysts and engineers.
These capabilities complement, rather than replace, the core management skills an MBA is built to develop.
What an AI-Ready MBA Means for Aspirants Today
For readers comparing programs, the useful question is not whether a curriculum mentions AI, but how it prepares you to apply technology to business problems. When evaluating a one-year MBA or PGPM, it is worth examining exposure to AI and analytics, the strength of the business analytics curriculum, case-based and experiential learning, industry interaction, cross-functional projects, consulting exposure, and opportunities to work on real business problems.
The Indian context underlines the point. According to figures cited by the Government of India’s Press Information Bureau, the NASSCOM AI Adoption Index scored India at 2.45 out of 4 in December 2025, with 87% of surveyed enterprises actively using AI solutions. Demand for professionals who can pair business understanding with AI fluency is widening, not narrowing.
This is where a program’s track record matters. The Great Lakes Institute of Management PGPM is designed to prepare graduates for an AI-led management profession, backed by a long pattern of curriculum innovation. Great Lakes was the first Indian business school to introduce Business Analytics as a major (2013), the first to offer Artificial Intelligence and Machine Learning as specialisations (2018), and has since built Generative AI, AR and VR into its learning pedagogy (2024). For experienced professionals who want cross-functional management skills alongside genuine AI and analytics exposure, that combination is exactly what an AI-ready program should provide.
Conclusion
The manager of the AI era does not need to build AI systems. They need to understand how AI can be applied to solve business problems, improve decisions and create value. That is a management skill, not a technical one.
For one-year MBA and PGPM aspirants, the takeaway is straightforward. The professionals who stand out will be those who combine management knowledge, business understanding, AI fluency and human judgement. As AI becomes a standard part of how businesses operate, that combination is likely to define what employers expect from their next generation of managers.
Frequently Asked Questions
Is AI important for MBA graduates?
Yes. AI is now used across most business functions, so managers increasingly need to understand how to apply it. MBA graduates do not need technical AI skills, but AI fluency — knowing where AI helps and how to interpret its output — is becoming a valuable complement to core management capabilities.
How is AI used in management?
Managers use AI to support data analysis, forecasting, market research, content creation, process automation and decision-making. The manager’s role is to frame the business problem, interpret AI-generated insights, apply judgement and decide on action — combining AI outputs with commercial reasoning rather than accepting them at face value.
What AI skills should MBA students learn?
MBA students benefit from AI and data literacy, prompt-writing for research and analysis, business problem framing, critical thinking, and responsible AI awareness covering bias, privacy and human oversight. The ability to collaborate with data and technology teams is equally valuable for turning business needs into practical solutions.
Can a one-year MBA prepare students for AI-driven careers?
A well-designed one-year MBA can help experienced professionals build cross-functional management skills alongside AI and analytics exposure within a shorter timeline. Outcomes depend on program quality and individual effort, so aspirants should examine the curriculum, experiential learning and industry interaction rather than program length alone.
Which business functions use AI?
AI is increasingly explored across marketing, finance, consulting and strategy, operations, human resources, sales, product management and supply chain. Applications range from customer segmentation and forecasting to demand planning and talent analytics, though adoption varies widely by organisation and remains early-stage in many companies.
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