How AI is changing business planning

Every organisation needs to plan. But with AI constantly changing, businesses need to improve their forecasting capabilities to adapt more effectively.

Our conversations with senior business leaders reveal two common challenges that are consistently top of mind: growth and margins. Many are working out how to grow in a tough environment, improve efficiency and do more with less in an ever-changing marketplace.

While the economic outlook is improving, there is still plenty of uncertainty. Regulatory and operational exposure ranges from the ATO and international tax reform to fluctuating trade policy, cyber threats, payroll compliance, evolving health, safety and environmental obligations, tariff volatility, and currency fluctuations, meaning businesses need to stay on the front foot.

Competitive advantage doesn't just come from predicting future events, but also from how quickly they respond when those events happen.

For Retail and CPG organisations, two of the biggest issues are managing supply and demand - getting supply right based on demand before it's too late is critical. Otherwise, you either end up with stock sitting on shelves, tying up capital or with insufficient inventory leading to lost revenue.

Another major issue the market faces is workforce planning. A sudden spike in demand may lead to last-minute hires at inflated wages. But if you hire extra staff in anticipation of peaks such as Black Friday or Christmas and they don't eventuate, you have the opposite problem.  There is a direct impact between the changes in one department and how it affects other departments down to the bottom line

Large retail and CPG businesses also spend millions and millions of dollars in trade promotions. They need to decide which products to discount, at what price, where and when, while understanding the knock-on effects. For example, discounting one product may cannibalise full-priced sales of another.  These challenges are very hard to scenario-plan for without technology.

All these decisions are connected. Increasingly, the question isn't simply, "What do we think will happen?" but "What if?" What if the cost of a resource goes up 50%? What if tariffs rise 15%? What if particular markets become inaccessible? What if we want to expand into different countries?

AI is changing this equation

As humans, we can only model so many scenarios, but AI can run thousands of "what ifs" with different combinations of events and their potential impact. This enables organisations to prepare for a much wider range of possibilities. Instead of responding after a change, they can understand in advance the actions to take and how decisions will affect the organisation.

Yet accurate and effective AI insights need quality data. If bad data is fed, only bad data will come out. AI can't magically fix business challenges without clean, complete, relevant and accessible data.  Not only do they need clean data, but to have this data on a platform with a calculation engine as the foundation so that the results from leveraging AI are deterministic as opposed to probabilistic.

Furthermore, connectedness and having visibility across the organisation is also critical. In an organisation where one department might be letting 1,000 people go while another is hiring 500, there may be people with transferable skills who could be retrained or moved into another role. Yet organisations often go through the cost of redundancies and recruiting, interviewing, onboarding, training and equipping hundreds of new people - just because they are unaware of what the rest of the organisation is doing.

Connectedness becomes even more important as organisations work out where AI fits within their workforce. It remains unclear which tasks AI will ultimately take over and how this will reshape jobs. Cutting roles on the assumption that AI will replace them, only to find that people need to be rehired later, can be a costly mistake.

Organisations need a clear view of how AI investments, workforce capacity and business priorities align, rather than making decisions in isolation. By integrating financial, workforce and operational planning, leaders can model different scenarios, assess AI's potential impact, and allocate resources where they will deliver the greatest value.

Ultimately, connected planning is critical for better decisions and, consequently, quantifiable business impacts. By identifying pressure points across the organisation, AI can connect planning processes, prevent unnecessary losses and improve responsiveness.

This doesn't mean AI investment will slow down, but we're moving beyond the initial hype cycle towards a smarter approach in which people leverage AI more thoughtfully. There should be a business case and a quantifiable return when thinking about how to leverage AI on a larger scale.

We can't know what the next tariff change, currency shock or regulatory change will be. But we can know what we'll do very quickly when it happens. Access to the right data, analysis and insights enables faster decisions, which are key to ultimately improving cost and margins and achieving success for the business.