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Artificial Intelligence is top of mind for every business decision-maker, and for good reason. Whereas earlier technology trends provided new capabilities for existing ways of working, AI has the potential to be more transformational, creating new ways of working. That promise, however, will take some time to fulfill, and until then, IT and business leaders need to become more grounded on where and how to start adopting AI today.

AI is about more than cost reduction

With businesses under constant pressure to reduce costs, this will often be the starting point with AI, where the automation of tasks and processes can yield cost savings. These savings will be well-received but could also give rise to the view that AI’s use cases should be built around driving operational efficiencies. This thinking is perfectly reasonable for businesses that want to be fully automated, but we have a long way to go until robots can replace all workers—and, is that something we really want to be doing?

Automation can drive a lot of business value, but work is still very much a human activity, and to date, AI can only address some aspects of what people do in the workplace. Communications is one of the best use cases for getting beyond cost savings when deploying AI. When AI is applied to communications, the net result is improved productivity, both for individual work and with teams. The impact here, however, is harder to measure compared to cost-based outcomes. To address this, IT leaders need to think about AI in terms of enhancing communications rather than improving the cost-effectiveness of workers.

Taking a people-first approach with AI

The transformative potential of AI is especially relevant today, as businesses themselves are being transformed and need to adapt to current realities. With an increasingly distributed workforce, communication technologies have never been more important. Workers need to feel empowered wherever they are located, and for AI to be effective, they need to trust the technology and feel that these new applications will help improve their performance. The best way to achieve that is through a people-first approach with AI.

Today’s information economy is driven by knowledge workers, where automation of mechanized tasks is less of a factor than the ability of workers to communicate with each other. The better those capabilities are, the more engaged they’ll be in their jobs, the more creative they’ll be working in teams, and more valued they’ll feel in your organization. Those are the outcomes that businesses need with hybrid work, and a people-first approach to AI involves focusing on these outcomes rather than the capabilities of the applications themselves. When AI can elevate the performance of your workers, that can have a transformative impact on your business.

Examples of a people-first approach to AI for communications

1. Automated transcription

During meetings or even 1:1 calls, the conversations can be transcribed, usually in real time. This is a great example of how AI can automate tasks, aligning well with decision-makers looking for efficiencies and cost savings.

A people-first approach would look beyond these face value benefits and focus on the outcomes that automated transcription would enable. When workers are freed from taking notes, they are more engaged—making eye contact, listening more intently, and enabling more focused conversations.

Once AI models become trained enough for workers to trust them fully—that will take some time, but it will happen—they’ll have accurate and complete transcriptions without the stress of trying to capture information during the call. The net result is a better meeting experience, happier workers, and inputs that will yield better outputs.

2. Meeting summaries

This application takes things one step further from transcription. By adding intelligence beyond speech-to-text, AI can extract the key takeaways from the meeting based on what the end user requires. Meeting summaries are another good example of AI-driven automation and, with a people-first, outcome-focused approach, they can also have a transformative impact on your business. AI applications are highly customizable, meaning that each worker can specify the type of summary they need from the meeting, such as discussion about a specific product, campaign, project, or team. They could request a high-level summary of the meeting so they don’t have to spend time watching the replay, or extract granular summaries that are pertinent to them.

These summaries allow workers to manage their teams and tasks more effectively, and that can be very empowering. In this context, AI gives workers a greater sense that technology is there to support them rather than control them.

3. Knowledge management

Converting information to knowledge ultimately requires human input, but AI provides the critical capabilities needed to manage today’s massive volumes of data. AI is built for large-scale data sets, and knowledge management addresses the challenge of effectively organizing and accessing information across the organization.

Without knowledge management, workers become quickly overwhelmed, which can greatly undermine the value of all the information that exists across the organization. A people-first approach would focus on the need for workers to leverage information for specific situations rather than just for general reference.

One example would be helping a worker prepare for a meeting, either with their team, a customer, a supplier, or even their boss for a performance review. Each would require specific inputs, and AI provides the horsepower to extract relevant pieces, doing so with intelligence.

AI can identify knowledge sources based on associations that the worker would not normally make themselves, as well as draw from both structured and unstructured data sets. These capabilities go beyond what humans can do. With this level of knowledge management, workers will feel in control rather than overwhelmed—and with that comes the confidence that inspires innovation and creativity, which are key ingredients for transformational impact.

A holistic view drives transformational impact

These are just three examples where AI can bring new business value for communications and collaboration applications. That value can be realized if viewed as a means to cost reduction and workflow automation, but that is only part of what’s possible with AI. For business leaders seeking a true transformational impact, a holistic view is needed—one that focuses on the human impact of these new technologies. By taking a people-first approach, the outcomes that the applications enable become the true barometer of change and will almost certainly have a greater impact on your business than any measure of cost savings that AI can provide.

Kira Makagon leads global product, user experience, engineering, cloud operations, security, and IT as RingCentral’s Chief Innovation Officer. She is a critical driver in defining RingCentral’s product strategy and in bringing to market RingCentral’s robust communications and collaboration solutions. Throughout her career, she has pioneered multiple breakthrough industry solutions and companies, garnering a reputation as a visionary product and business leader.