Matt Lumins, head of customer success for Europe at Intradiem, argues that data, AI and automation can empower humans, but they can’t and should never replace humans.
We’ve all heard scary stories. With infinite data available, organizations can become less dependent on human labor. Artificial intelligence (AI) will become smarter than humans. And automation takes away many of our jobs.
But how true is this? These technologies, such as conversational AI, are advancing, but they are just tools to make our lives easier and our organizations more productive.1
But even tools with contextual and conversational capabilities can’t offer the unique flexibility and sheer ingenuity of humanness that we all want and admire. it is in our nature.
A question arises here. How can we continue to make the most of them in our work and in our lives? The answer lies in using them to empower us. In doing so, they will free us up to do what we do best.
Communication, connecting with people, empathy, and ultimately problem solving – AI can solve any problem we can think of, but it can’t come up with a problem we can solve.
In other words, we need them to be data-driven and technology-driven to leverage them to serve us, but not replace us.
To achieve this, leaders should focus on three things. First, we need to understand what data is available.
Then we need to figure out how to make sense of it using AI and machine learning (ML). Then we need to consider how automation can be used to take on simple tasks that we are least suited for.
Understand available data
The first step to empowerment is as much as understanding what information you have, where it resides within your business, who has access to it, and if there are holes that limit the effectiveness of your information. it’s simple.
Identifying the biggest challenges facing your organization is a good starting point for determining which data has the most value. For example, is it difficult to get a single view of the customer because communication happens through many different channels? Understanding the problem is the first step to solving it.
Once companies have resolved these challenges, they must obtain a solution for collating and analyzing interpretable data. Finally, we need to ask the right questions by creating the right hypotheses that data analysis supports solving. The importance of human involvement at every stage of that journey cannot be underestimated.
To achieve the desired results at scale, organizations must build a data-centric culture from top to bottom.
This may sound like an executive story, but it really means making sure everyone understands that the best decisions need to be based on data and insights. .
Also invest in a variety of professional roles such as data engineers, data visualizers, and data analysts who identify, collect, organize, explore, and report on data from various systems to provide business insight. is also required.
These resources cannot be siled in a think tank bunker somewhere in your organization. No, to be effective it must be integrated with the operational business team and have access to change and process experts.
Get the facts: AI and ML
But, of course, this is easier said than done. Data is not always easy to understand, even for data analysts. Also, most businesses today generate millions of real-time data points that humans can’t hope to understand while on the job. And they shouldn’t even try. It’s not what they do best.
This is where AI and ML come into play. These algorithms allow you to filter your data and present it in an easy-to-understand way. For example, dashboards, maps, charts, etc., rather than spreadsheets and tables.
And, as anyone in the industry knows, the software is incredibly fast. Theoretically, the latest technology allows AI to learn and act at the speed of light.2 Widely available AI software may not have achieved this speed yet, but it will show how fast it can be.
To understand this in a little more detail, imagine a customer service team working for a large company. Agents are constantly creating vast amounts of data, including customer data and data about themselves. The latter may include information not only about when and through which channels the customer will contact you, but also about the customer’s own work patterns and performance.
With the right tools, AI can sift through information almost instantly, noticing trends and stress points, such as work peaks and valleys, whether someone needs a break, or whether additional support or training is needed. to understand things.
When recommendations are presented to managers on dashboards, managers can make informed decisions about what to do instead of relying on intuition.
In some cases, automating these recommendations and notifying managers can save time and effort and achieve the same results. This can have a positive ripple effect on customer and team morale.
Automation technology can perform tasks that are not optimal for us
So it’s clear how data can be searched, understood and presented to help people make better decisions. The next step is to add automation to your mix. Imagine again the example of a manager with many dashboards in front of him.
Managers can stare at graphs and charts all day, wait for a red light to appear, or even keep making small actions with their team. Perhaps give someone a break or change the route of work.
Or automated software can do it, using insights from data and AI. Anyone taking longer than usual to serve customers? Maybe they’re tired and struggling. Allow automation to schedule quick breaks. Insufficient customer feedback or insufficient NPS comments? Automate some support actions, such as refresher training programs and targeted coaching sessions.
Automation can take over almost any manual task, and the applications are endless.
Invoices can be processed by the finance team. Route customers to the best agent. Information can be collected and included in departmental reports and email triage.
Combined with AI, it’s like having a digital assistant take over time-consuming, repetitive tasks that waste your time and keep you from doing your best work.
The future of AI and automation is human-centric
These technologies are not new, but they continue to advance rapidly. This provides an opportunity to harness them to solve some of the biggest challenges in society and business. But we will only succeed if we remain masters of technology, not servants.
By using AI and automation to empower people, not replace them, organizations can be data-driven, yet technology-driven and put people at the center. These software are tools that help humans do their best work and eliminate manual tedium.
And it makes perfect sense. There will always be a defining moment where a human must be involved at a critical point, so in an automated process he might be 75% human doing the work, but the rest would need to be completed by a human. I have.
And the more we can focus on that 25%, the better the results will be for our employees, our customers, and the organizations that connect them.
After all, anyone who tries to take people out of the equation is doomed to failure. Because we are human by nature, people will always be the most important resource for an organization. The key is to leverage intelligent technology to help you achieve more.
This is why data, AI and automation cannot replace humans.
References
- https://venturebeat.com/ai/how-chatgpt-in-microsoft-office-could-change-the-workplace-the-ai-beat/
- https://www.independent.co.uk/tech/ai-machine-learning-light-speed-artificial-intelligence-a9629976.html
