Three myths about AI in business

No, AI is not taking jobs or reducing human interaction, says Richard Jones of Confluent
Richard Jones
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In 2024 there seems to be no escape from discussions about AI in business. One minute AI is creating whole new industries, the next it’s taking all our jobs. First, it’s saving businesses money, then it’s plunging companies into unexpected lawsuits. Some say it’ll bolster the UK economy, while others tell us it’ll end capitalism for good.

No wonder everyone’s so confused!

For those of us working in tech, AI is a tool. It’s a way to quickly access, structure and present data for maximum use and understanding. Used well, that can only be a good thing. But due to the torrent of information (and misinformation) surrounding AI, an understanding gap is emerging — a gap between what businesses imagine AI will do, and the impact it will actually have in the real-world.

In this article I wanted to explore a few of the biggest misconceptions that I regularly encounter from businesses, employees, and even customers, and consider whether the hype – and hysteria – around AI is justified.

Misconception 1: AI is taking jobs

The Misconception

One of the most widespread fears is that AI and automation signify the end of human employment as we know it. Images of robots manning assembly lines or AI systems managing customer inquiries fuel concerns that machines are poised to replace employees en masse, leading to widespread unemployment.

The reality

The truth, however, is more nuanced – and far less dystopian! 

While AI does automate routine tasks, it simultaneously creates new opportunities and enhances existing roles. In almost every enterprise sector, AI is fostering new roles that didn't exist a decade ago, such as machine learning developers, prompt engineers and data scientists.

By taking over mundane tasks, AI allows existing employees to focus on complex, creative, and strategic activities that add greater value.

As a result, many employees will get to reclaim the time and energy eaten up by boring, time-consuming admin, and reinvest it elsewhere. Job roles will gradually change to put more and more emphasis on human interaction and informed decision-making. That will require many to upskill, as they grow into these new roles – which will often be evolving on the fly. 

Ironically, AI won’t replace people – it will make them better, more rounded employees.

Misconception 2: customers will receive less human interaction

The misconception

Another common concern is that as businesses increasingly deploy AI in customer service roles, the lack of human interaction will lead to impersonal and unsatisfactory customer experiences. Critics argue that machines can’t replicate the empathy and understanding that a human can provide, potentially damaging brand loyalty and satisfaction.

The reality

Contrary to this belief, AI has the potential to significantly enhance customer experiences. AI-powered chatbots and virtual assistants can provide instant responses 24/7, addressing common queries and problems without the need for human intervention. This immediacy and efficiency can significantly boost customer satisfaction.

At the same time, AI can analyse vast amounts of data to deliver personalized recommendations and services, something that is increasingly expected by consumers. When combined with data streaming technologies, this can be achieved in real-time, building customer service applications that respond accurately, in real-time, and in a human way.

When AI is used in conjunction with human agents, it can free up humans to handle more complex and sensitive issues, thereby improving the quality of service. Many businesses report increased customer satisfaction scores after integrating AI into their customer service processes, demonstrating that technology can enhance rather than detract from the human experience.

Misconception 3: AI is a 'wild west' lacking regulation

The misconception

Another common concern for businesses is the idea notion the field of AI, particularly in business applications, operates in a 'Wild West' environment devoid of regulations, standards, and ethical guidelines. As a result, many business leaders worry that unchecked AI deployment could lead to potential misuse, privacy breaches, and a loss of control over corporate data.

The reality

Contrary to the 'Wild West' image, the AI industry is progressively moving towards a framework of governance, ethical use, and regulation. While that framework develops however, it’s down to businesses to ensure they use AI responsibly.

A lot of this comes down to the actual data we use to feed AI. Do you provide it with access to every piece of information across your business? Is process compliant with your regulatory requirements? Do customers (and employees) have a right to know you’re training AI with their data? These are all essential questions that need to be asked.

To address this, many businesses are adopting ‘stream governance’. This process allows businesses to feed their data into AI, in real-time, but while keeping it within the boundaries of pre-agreed rules and regulations. Without getting too technical about it, this essentially ensures that a business’ use of AI adheres to predefined data policies and ethical standards. 

Winners and losers

If there’s one key thing to take away from the above, it’s that AI in business is not a zero-sum game where machines win, and humans lose. Instead, it's an evolving partnership where AI augments human capabilities, making businesses more efficient, innovative, and responsive to customer needs.

The real question for businesses in 2024 isn’t whether they choose to embrace or reject AI. AI is a tool with unmeasurable benefits, and it’s coming whether we like it or not. 

The real question is how we choose to feed AI. How we make ethical and conscious decisions about the data we input into these systems, and the level of access we provide them with. AI is only as good as the data it’s trained on, so perhaps in 2024 we should talk less about artificial intelligence, and more about the quality, and responsibilities, that surround our data.

Written by
Richard Jones
Written by
February 8, 2024