Finding the Right Fit for AI
Companies today have an unprecedented amount of valuable customer and employee data – information that can be made available to any device, anywhere. They face a challenge, however, in extracting and interpreting all this data in real-time to drive business benefit – be it to better serve their customers, improve products, or drive efficiencies.
Any company that can find a better way to leverage their data can steal a march on their competition, and in some cases their survival may depend on it.
“Many see AI as a solution to harness and monetise all this information, but advances in automation and machine learning will only help humans to better leverage data to make more timely decisions, better aligned with the needs of their business.”
This approach to AI, wherein machines enable people to work in more efficient, meaningful ways, is known as Intelligence Augmentation, or IA. It’s an idea that highlights AI’s potential to help individuals become more agile and effective in their roles. And there’s a lot to be gained by adopting it as a company-wide strategy.
A Gartner report identified that the greatest business value AI will provide in the coming years is decision making support, not process automation. Organizations will see the most benefit from AI implementation strategies that aim to better engage, rather than replace human employees. The report further projected that IA will drive net job growth, generating an estimated $2.9 trillion in business value and recovering 6.2 billion hours of worker productivity in 2021.
Some key industries are already seeing the benefit of Human-AI collaboration. Global contact centers are using Natural Language Processing (NLP), to listen to and identify patterns in interactions. NLP and sentiment analysis can be used to monitor emotional levels on a call in real time, and to identify known red flags, so the agent can be given advice on how to handle the situation in the moment, or allowing the call to be routed to a supervisor who can intervene before a negative outcome is realised.
Insights generated by applying NLP to large volumes of calls, analyzed with machine learning, can be used to generate successful scripts, training materials, and real-time assistance for agents. In this way, AI is able to make the organisation’s collective depth of insight and emotional intelligence, gleaned from huge volumes of experience from their best – and worst – agents, available to every agent on every customer interaction. Making AI-generated best practice generally available can raise the performance of the entire team, or even help bridge cultural divides for employees in offshore locations.
“In the customer services space, AI can help to make interactions more human. The identity verification process, loathed by customers for its seemingly endless manual security prompts, can be simplified and streamlined by speech recognition which allows the system to recognise the customer in a more natural way.”
AI can also structure interactions to maximize the customer’s convenience, as agents equipped with tailored information on an individual’s needs can reach out proactively in ways that fit the customers’ schedule and preferences. Based on history, the customer’s pre-defined preferences, or the specific situation, interactions can be scheduled or on-demand, self-service or fully supported, and through text, voice, or video, on any device, or a combination of these. Interactions enabled in this way improve not only customer satisfaction and brand image, but also employee experience and overall business productivity.
Connecting the Workplace
AI can be applied in similar ways to day-to-day business communications in global organisations with connected, mobile workforces. Collaboration technology has already brought diverse, global teams closer together, creating new opportunities – and also new challenges – to effective communication.
“Usage of these technologies and the need for improving their effectiveness have only increased with work-from-home measures in response to the global pandemic.”
NLP and AI can already improve efficiency by transcribing meetings, making recordings indexable and searchable, and generating meeting minutes and action lists.
But given the global nature of business, conferences calls often require advance knowledge of diverse customs, sensitivities and, potentially an understanding of foreign languages. AI can also be used to generate profiles of meeting participants and to refine talking points based on publicly available information. In the meeting itself, NLP could be used to process multiple languages and translate in real time, adding suggested nuances or context to points made. As in the call center example, AI could use sentiment analysis to identify emotions or cultural sensitivities and suggest alternative responses in real time. We’re only beginning to scratch the surface on potential applications, but the common denominator is clear: AI represents a tremendous opportunity to facilitate and enhance, not replace, person-to-person collaboration.
The above examples are admittedly generic and could be applied to any industry. We have not even begun to talk about the application of AI in specific contexts of vertical industries or leveraging AI and myriad data generated by IoT to enhance and extend human capabilities. That may be a topic for another day, but in the meantime, one thing is clear: AI represents a tremendous opportunity to magnify the impact of the organisation’s collective human capabilities and knowledge to differentiate, hone competitive advantage, and transform customer and employee experience.
Discover more about how tech such as AI is making the world a better place.