Dec 13, 2022

How AI is Transforming Business Decision-Making

Discover key steps of effective decision-making: problem identification, information gathering, alternative evaluation, and implementation planning.

Artificial intelligence (AI) is fundamentally changing how businesses operate and make decisions. By analysing massive amounts of data, identifying patterns, and making predictions, AI gives companies an unprecedented ability to optimise decisions and improve performance. Here are some of the key ways AI is transforming business decision-making:

Predictive Analytics

One of the most powerful applications of AI is in predictive analytics. Sophisticated machine learning algorithms can continuously analyse data to find correlations and make forecasts about the future. This allows businesses to get ahead of challenges and opportunities. For example, retailers can use AI to predict customer churn, personalised promotions that will resonate most with each customer, and optimise pricing for maximum revenue. Manufacturers can anticipate disruptions in their supply chains before they happen. Healthcare systems can use AI to predict flu outbreaks or model the spread of infections. The applications are endless.

Prescriptive Analytics

In addition to predicting future outcomes, AI can also recommend the best course of action to achieve goals. It can take into account constraints, risks, and multiple objectives to prescribe optimised decisions. For instance, AI can adjust staffing levels at call centres based on predicted call volumes. It can recommend portfolio allocations tailored to an investor's risk appetite and return objectives. AI can also suggest cost-optimised shipping routes accounting for fluctuating fuel prices and weather conditions.

Automated Decision Making

AI is also being used to automate high volume, routine decisions. This saves time and frees up human workers to focus on higher value judgements requiring creativity and empathy. For example, banks use AI chatbots to address common customer service enquiries. AI approves routine transactions like point-of-sale purchases and processes simple claims. AI also optimises logistics by automatically scheduling shipments, routing lorries, and reordering inventory.

Risk Modelling

Because AI can rapidly analyse millions of hypothetical scenarios, it is very effective at modelling risks. Banks are using AI to stress test loan portfolios and model credit, market, and operational risks. Insurance firms are using AI to assess different risks, set premiums, and detect fraud. AI simulations also allow companies to stress-test strategies against different competitive scenarios.

Game Theory

In competitive markets, AI uses game theory to predict strategic scenarios and recommend optimal approaches. It can run competitive simulations to find ideal pricing levels, marketing strategies, or product features that maximise market share. AI models help companies make the right strategic decisions in dynamic, competitive environments.

The Key is Integration

To fully benefit from AI, companies must tightly integrate it within existing workflows and processes. Humans must work symbiotically with machines to augment expertise rather than replace human judgement. With a thoughtful implementation framework, AI can significantly enhance the speed, accuracy, and efficiency of business decision-making.

Getting Started with AI

Developing full-scale enterprise AI solutions requires technical expertise that many companies lack. A pragmatic approach is to start with a proof-of-concept or minimum viable product focused on a single use case. This allows companies to run trials, develop insights, and expand on success. With deliberate experimentation and patience, AI can transform decision-making and deliver exponential returns.

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