In the last decade, artificial intelligence has matured from a novel, fast-emerging technology to one embraced by every industry around the globe. And in the last few years, workplaces have increasingly become remote or hybrid, accelerating the amount of data being created, consumed, and scrutinized daily.
But remote work has made quick in-person communication more challenging, causing many traditional organizational practices to fumble. Workers increasingly rely on a growing amount of data accessed, processed, and organized across networks.
These trends have prompted companies to rely on technologies like AI to bring workers together and help managers lead them more effectively.
As the CEO and co-founder of Katana Graph – and having spent decades in academia before that – I’ve seen how AI has flourished, thanks largely to the vast amounts of data being accumulated worldwide. Most of this data is unstructured, providing a clear need – and opportunity – to better understand the relationships between the entities in these data troves and to analyze them quickly for tangible and actionable insights.
Here are three examples of how organizations can reap the benefits of AI technology.
1. Making remote work more seamless
In a survey of 1,000 employees a few years ago, 49 percent had difficulty finding documents. Further, IDC found that employees spend five hours a week searching for documents on average. Unfortunately, with the increase in remote and hybrid workplaces, some argue the problem has worsened.
[ Also read Using automation to improve employee experience. ]
How can AI help? AI can analyze workflows and collaboration tools to provide more streamlined and efficient processes. A recent piece on modernizing work through digital collaboration discussed remote employees’ desire for improved connectivity with their colleagues. Here are just a few ways companies can use AI to improve workflow and collaboration:
- Enterprise-grade digital assistants with conversational AI help make meetings a zero-touch experience
- Distributed collaboration for colleagues with greater contextual insight than in-person meetings, such as surfacing background material online without performing searches.
- Embedded cross-product AI functionality to identify details of the last conversation in a meeting. Alternatively, AI can transcribe meetings and distribute a voice-searchable version to those not in attendance.
2. Funneling data to improve workplace training
Strong leaders and remote workers realize the importance of skills and training in today’s competitive job market. Training is one of the best ways to manage remote workforces. In my experience, AI can help significantly in this area, particularly when leaders harness the power of machine learning.
Some organizations are already incorporating the power of AI into skills training and other employee development initiatives. For example, they’re using no-code software platforms to contextually guide new employees on how to use systems, minimizing the need for workshop-styling training. The shift to remote and hybrid work has increased the use of tools that help employees complete training more independently, with fewer meetings or workshops.
To be effective, AI must use information that will produce the best results. Human-in-the-loop systems are a critical part of any competitive advantage and are necessary for any socially responsible artificial intelligence/machine learning system. Human ingenuity must be deeply embedded into intelligent systems.
3. Ensuring quality service
A third area to harness the power of AI is with your customers. AI can help unite your workers toward a common goal: to uphold customer satisfaction through quality business performance and improved customer insights. Ultimately, this is a key element of how AI can support business growth.
Is AI becoming the new customer service agent? It is certainly helping organizations of all sizes improve customer satisfaction. Companies can use AI to provide employees with insights from customer service data that enable them to improve their processes.
AI’s data analysis is also useful in the financial sector, where it helps safeguard customers’ assets and improve customer service. By monitoring a checkpoint system that verifies transactions, AI can flag fraud in real-time, protecting customers’ funds and boosting satisfaction. Furthermore, the transaction data can help institutions better understand their customers.
AI can help organizations unite workers around common goals and improve operational efficiencies. By focusing on key areas for remote workers, AI systems can analyze huge amounts of data and provide actionable insights that help employees succeed – no matter where they physically work.
[ Check out our primer on 10 key artificial intelligence terms for IT and business leaders: Cheat sheet: AI glossary. ]
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