Which business sectors might we anticipate Artificial Intelligence In The Future transforming in the coming ten years? Most of them, according to specialists. Here are twelve to kick off the revolution:

 Artificial Intelligence In The Future
© Artificial Intelligence In The Future

Artificial intelligence (AI) has cemented its reputation as a “must-have” technology, allowing businesses to go further and quicker than their rivals in order to improve real-time pricing or stock control or make forecasts that are more accurate.

However, as we noted in the November edition of Technology Magazine, the majority of boardrooms and executives are still unsure of the possible applications for artificial intelligence (AI) and machine learning (ML). Elliott Young, CTO of Dell Technologies UK, claims that “stakeholders frequently don’t know what to ask for in order to get the right benefits out of the technology.” This implies that they are unaware of potential benefits to their company.

Anthony J. Bradley, Group Vice President of Emerging Technologies and Trends Research at Gartner, claims that overhyped AI scares consumers and hides the true advantages that these technologies may provide. This might result in delayed acceptance, as well as sociopolitical dread and government restriction that would limit advancement.

Six industries that will receive a lot of attention in the future are examined in further detail.

1.Forecasting and predictions
2.Insurance and Risk
3.Marketing and Sales
4.Defence
5.customer Encounter
6.Investment and Asset Management

1.Forecasting and predictions:

According to Sian Townson, Partner, Oliver Wyman, AI is transitioning from its current position as a technology that spots relationships in data and more accurately predicts current trends to a technology that spots future shifts in everything by analysing preferences and sentiments, from leisure spending and travel patterns to company creditworthiness.

“As AI model explainability improves, along with more trustworthy ways to monitor performance, robustness, and fairness, these more complex models have in turn become more reliable with their methods and results more understandable, hence more feasible and creative applications,” she continues. By establishing links between embedded traits, AI can identify disruptors.

2.Insurance and Risk:

Machine learning (ML) will read through forms and review voice and video recordings, highlighting where the reviewer’s attention should be focused, how a call should be routed, or simply if an attachment has been forgotten, according to Oliver Wyman’s Townson. This will increase efficiency and fairness in areas like credit risk, insurance, human resources, and conducting surveillance.

Some businesses will also utilise AI to enhance their customer service, actually making operations more transparent and objective. “AI is used to automate customer-facing steps, from chatbots to processing an order.”

Even while defining fairness can occasionally be a difficult first step, AI-based techniques can now be more egalitarian, transparent, and objective than earlier human attempts, according to Townson.

“Even uncontrolled, AI does not necessarily make a process less fair,” the author argues. “AI stresses just how unjust these prior judgements were by mathematically attempting to duplicate them. Now, we can use that power to reduce some of the imbalances we are now experiencing.

3.Marketing and Sales:

Conversational chatbots are a particularly high-profile application of AI and are currently a common element of the user experience on most websites. However, the sales and marketing sector stands to benefit greatly from machine learning in the future.

According to Townson, artificial intelligence helps businesses to execute activities and change their plans in real-time. In the meanwhile, machine learning algorithms will automatically boost sales campaigns or postpone the release of items that can cannibalise sales from other product lines.

In other words, AI can adjust these kinds of choices to bring in more revenue, even from previously unpromoted goods.

4.Defence:

The defence sector is going through some significant changes,” claims Townson. There is definitely room for acceleration once they can completely implement their AI risk governance.

Over a thousand AI-related tasks are now being actively developed by the US Navy. According to Brett Vaughan, Chief AI Officer for the US Navy, “I think most would be surprised to the degree with which AI is being groomed and developed within the Navy.” “However, the majority of these initiatives are in the R&D sector. We are thus targeting the faster development of such skills to the fleet in the highly technology and competitive environment of the current day.

Vaughan can only reveal so much, but he confirms that the US Navy is using AI in two areas: allowing autonomy in unmanned/robotic systems and enhancing the calibre and speed of human decision-making.

5.customer Encounter:

According to IDC’s Future of Customer Experience research, during the next four years, nearly half of the major corporations in the world will be transforming their customer experience (CX) through the use of AI and ML.

“In a world of accelerated uncertainty, the next era of CX innovation will be led by those brands that improve value for the customer through empathy and delivering outcomes for customer success,” asserts Sudhir Rajagopal, Research Director, Future of Customer Experience at IDC.

According to the IDC analysis, by 2026, 45% of the Global 2000 are anticipated to utilise AI/ML to guide customers towards unique, unfamiliar experiences in order to boost sentiment metrics and brand upselling opportunities.

According to Paul Henninger, Head of Connected Technology at KPMG UK, “AI technology is already sophisticated enough to transform how customers interact with companies and government.” Large language models, conversational AI, and AI-driven avatars are now being researched, and when they are used, the interactions between consumers, their data, and corporate services will be completely altered.

6.Investment and Asset Management:

Since manual checks are slowing down operations due to a lack of experienced compliance workers, more than two-thirds of banks view AI and ML technologies as essential tools for addressing the growing complexity of trade surveillance.

According to a recent survey by Acuiti, global financial businesses are turning more and more to technology for efficiency, with a clear need for more automated workflows. This trend is being driven by regulatory requirements and made worse by volatility.

According to Henninger of KPMG, algorithmic trading has already changed trade in several ways. The way we approach achieving our retirement goals and the sorts of results that investors want to be a part of will both undergo the same total upheaval, according to the prediction.

“The asset management industry will undergo a massive transformation in the next ten years, driven by AI that works for the investor, asset management, and other computational and tokenization technologies,” predicts Henninger.

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