AI technologies have evolved tremendously in recent years, and it’s not just ChatGPT to help with creating content that deserves the spotlight. AI is transforming business management by helping organisations do more with less across various functions, from recruitment to project management and even customer service. 

Here are five ways that AI is shaping business management today. 

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1.   Enhancing customer relationship management 

AI can help you analyse and organise customer data, make important predictions, detect buyer intent, and much more. You’ll get the most out of AI if you use AI technologies with the right infrastructure – like a CRM. That’s because the CRM acts as foundational infrastructure, hosting important data including conversations, customer profiles, interactions at various touchpoints, and more. 

AI can help you make sense of this data, such as with sentiment analysis or pattern recognition. This way, you can lead with data-driven decisions. It’s also useful for automating repetitive tasks, like migrating data across different systems or automatically updating customer information.

2.   Optimizing project and task management

Harvard Business Review believes that the abysmal 35% average success rate of projects can be drastically improved with the help of technology, including artificial intelligence. In other words, it’s time for businesses to ditch the spreadsheets and slides for project management and move toward more mature systems that are complemented by AI. 

If you have the right tech infrastructure in place, AI can automate and improve various tasks. For example, it can assign resources to projects and tasks based on their previous performance, skills, and experience, ensuring you have the right people for each job. AI can also estimate budgets, forecast resource requirements, help identify bottlenecks, analyse past projects, and much more.

Gartner’s research estimates that as much as 80% of project management tasks will be run by AI by 2030, so AI adoption is necessary to stay competitive. 

3.   Analyzing data and forecasting

AI and machine learning (ML) tools can analyse large sets of data to analyse patterns, grasp sentiment, and yes, make forecasts and predictions. When you combine AI with your existing systems, like your project management tool, CRM, business management solution, etc., then it can pull and analyse data from your existing systems for forecasting. 

For example, it might predict your expenses for Q4, or your hiring needs for the next year. It may use, say, your historical data (e.g., how many resources were required for previous projects) and projections (e.g., how many projects you’ll have in Q4 and the nature of those projects) to estimate these needs. 

4.   Enhancing cybersecurity

Interestingly, AI’s traits – namely its ability to keep learning and to recognise patterns – make it a powerful tool for protecting businesses from cyber threats. For example, AI can:

  • Accurately categorize your IT inventory. What tools are you using, how many users are there for each, how many devices does your organization have, etc.? AI can aggregate this data for you, so you know exactly which systems to manage and monitor.
  • Provide suggestions for incident response. How should you respond to a security alert, and what threats should you prioritize? You can train AI to learn and provide data-driven suggestions to mitigate risks as they arise.
  • Monitor threat exposure. You can use AI not only to monitor your systems for potential threats and malicious activity, but also to watch out for likely attacks. If there’s a sudden wave of a particular kind of cybersecurity attack (hackers follow industry trends, just like everyone else), then your AI can prepare for it.

5.   Improving talent acquisition

AI in talent acquisition is not something to sleep on – it can do so much more than just screen resumes (although that’s quite helpful, too). You can also use it to, say, find the best time to schedule interviews, proctor assessments to ensure fair play and assess applicants across various metrics. 

However, it’s important to see where AI can add real value in recruitment, as opposed to trying to fit it in everywhere. For example, while you might use AI to score applicants on various metrics, you might still want to interview the candidates in the final round, after the initial screening. 

How is AI shaping your business?

As AI continues to evolve and mature, businesses can leverage the technology to achieve new productivity gains. But implementing AI in business management isn’t a plug-and-play process; you need to intentionally consider your systems and processes, and assess where AI can add real value. 

So, how is your organization using AI – and what future plans do you have for the technology? 

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