Welcome back! This is Part Three of my four-part series on the future of communications for manufacturers. If you’re just joining the series, Part One reviews research on the communications channels that companies consider most important going forward, and Part Two uncovers the communications analytics that companies are using to support their future plans. For this discussion, we’ll look at research that explores the use of AI with business communications. The results are quite startling—so lets dive in.

In 2018, we gave a presentation at Google Next. In that session, we quoted a Gartner statistic revealing that only 4% of CIOs globally had AI in production - for any reason. We also shared 8x8 research showing that 78% of companies believed AI would impact contact centre applications in the next two years. But, 64% felt that AI was still mostly hype and would have little impact on customer experience. The fun part: 77% were planning to deploy AI capabilities in the contact centre anyway.

The quick transition to AI

To find out what actually happened, 8x8 conducted new research. The response was startling: 72% of companies had deployed AI with their business communications and another 25% are in the process of doing so. In just three years, companies had gone from just 4% deploying AI for any reason to 97% deploying AI with business communications. All that news about digital transformation acceleration seems to be accurate!

You might be thinking that everyone deployed chatbots. Given the acceleration of digital engagement capabilities over the last two years, that would be a reasonable hypothesis. Once again, I was startled by the types of AI capabilities deployed in the last six months:

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It’s important to note that many companies had already deployed some of these capabilities more than six months ago. That explains why, in the last six months, chatbots have the lowest percentage; most companies have already deployed them.

We asked which AI capabilities they plan to deploy in the next three months. It seems that companies are now shifting into high-speed, four-wheel drive:

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What’s driving this rapid deployment of AI capabilities with business communications? Essentially, companies are working hard to provide employees with the tools they need to deliver an exceptional customer experience. The past two years taught us all the importance of this point, as well as how fast it can actually be done when made a priority.

To uncover the motivations driving this rapid transition, respondents were asked to select their top three reasons for adopting AI-based capabilities. The resulting top four selections are all about employee empowerment. They range from improvement of customer service capabilities and workforce management to making our jobs easier (couldn’t agree more) and getting rid of manual, repetitive work.

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At this point, the data has been very clear: AI is not just hype. With such rapid adoption across a broad range of topics, AI has quickly moved into the mainstream. A key reason is that companies believe that it will improve their business. Specifically, it helps staff address customer issues while also enhancing productivity. The practical application of AI is being used to augment people, not replace them. I’ll save the data about the social impact of AI for later in this discussion, but the research results are very motivating—AI is being used as a helpful tool.

There’s also a much deeper rationale that is motivating companies. People believe that the use of AI capabilities will revolutionise business communications. Consider how AI is characterised at your company. Given the results of this data, your organisation is probably already using AI in some form with communications.

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Take a moment to ask yourself:

  • What impact has the pandemic had on the role of communications in your organisation?
  • Are communications now a strategic-level topic?
  • If your company had to scramble and put new capabilities in place to enable remote working, are investments being made to move forward with a more coordinated approach?
  • Is an enterprise architecture perspective being used to plan communications capabilities, or are business phone, contact centre, and video capabilities still being handled as discrete topics?
  • Where is AI in the planning?

There is a data point in these results that should cause a little anxiety: 71% indicate “My company is always looking to implement new AI.” Seven out of ten companies are already at the point where they are constantly looking for new ways to invest in AI capabilities with business communications. Is your company at this level? If not, any concern about falling behind? Sixty-eight percent of companies believe they will fall behind if they don’t adopt AI. The takeaway is that communications need to be a core part of strategic planning and efforts to strengthen organisational resilience. As part of that discussion, I would recommend AI capabilities be considered a top priority as it’s clear that they are an important component in the future of communications for every company, including manufacturers.

Challenges and learnings

Of course, it’s not as simple as just plugging in some AI and off it goes, driving better customer experiences and making people more productive. To better understand the challenges companies faced when deploying AI capabilities, we asked them about the difficulties related to deployment and what they found to be keys for success. The responses are quite interesting.

Starting with the success criteria, there are no surprises here except the importance of transparency. Companies found that over-communicating and being very open about the AI project was the most important success factor. This point is important for any project, but it’s extraordinarily important for AI-based projects given all the hype and misunderstandings about this topic. Amara’s law also plays a role here as people have a tendency to overestimate the impact of new technology in the beginning. Being transparent from the start will ensure that expectations are appropriately corralled.

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Of course, we can’t have a discussion about AI without addressing data readiness. Note that it’s pervasive in all of the success criteria. Building a working algorithm, identifying customer issues, integration with current systems, data privacy, real-time support, and ethical implications all involve data readiness. Although there are several aspects to data readiness, it starts with getting the data organised.

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In Part Two of this series, I describe the five main data types, their uses, and the systems needed to get data into a usable condition. If you can’t aggregate the data so it’s complete, accurate, and timely, it will be difficult to support AI capabilities.

Starting with a very specific use case helps to ensure success and provides another example of why transparency is so important. Specific use cases involving AI capabilities will not be like Jeff in the movie “Finch,” but they may make it easier for customers to check if you have a part in stock much faster and without human involvement for such a routine task.

The research has an entire section on the learnings from companies that have experience deploying AI capabilities with their communications. Including it all here would turn this post into a lengthy dissertation. If you’d like to avoid some scar tissue and make new mistakes, connect with me on LinkedIn and we can set up time to review the additional insights.

Ethical concerns about the use of AI

It’s impossible to do this topic justice in this format. It also seems irresponsible to exclude it. At the risk of doing a responsible injustice, let’s take a quick look at how companies are thinking about the ethical concerns related to AI.

Ultimately, companies are concerned about the malicious use of AI along with the potential impact to privacy. The good news is that companies are explicitly acknowledging these concerns and working to ensure that AI does no harm.

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Sentiment analysis is based on the language used during calls and chats. It’s a powerful tool to understand the topics most important at that time or to better assess current attitudes about a specific topic. We did a quick sentiment analysis experiment with this research to better understand how people deploying AI capabilities with their business communications felt about it. We asked them to select the terms that best describe AI-based capabilities. The results are quite positive. Overall, AI capabilities are considered necessary, helpful, profitable, secure, but maybe not as simple as everyone would like. Is there an unexpected term in the list? Profitable surprised me, but in the context of this research, it makes perfect sense as companies believe it will revolutionize business communications with 74% indicating that it will increase company profitability.

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As with any important topic, being transparent and explicitly addressing possible challenges and negative impacts ensures more productive outcomes. So far, companies appear to be elegantly managing this technology. It’s also clear that AI-based capabilities are a key part of the future of communications for manufacturers. The question is: where is your company on this topic?

There’s a lot more information from this research that I would be happy to share with you. If you would like to learn more, I can be reached on LinkedIn or please feel free to schedule a call.

Stay tuned for the fourth and final installment in this series, where I’ll explore how the decision-making process has changed for cloud communications projects. For example, the research highlights very interesting insights about whether or not the process is different when buying standalone unified communications or cloud contact centre applications versus buying a comprehensive communications platform.