The past decade has been transformative for artificial intelligence (AI).  Driving what many have termed the 4th industrial revolution, AI technologies can now be found across industries and functions. Does artificial intelligence really play a role in an organisations’ growth however and is understanding its future really that important?

The status of AI today

While artificial intelligence used to be a recurrent theme in science fiction novels, AI systems have become mainstream. Artificial intelligence and machine learning are no longer only of interest to the select few working in science. AI is everywhere and is applied to:

Levels of AI investment remain healthy despite COVID-19. According to Gartner, 42% of business and IT professionals have continued to spend on artificial intelligence. The IDC Worldwide Artificial Intelligence Spending Guide showed investment reach $50.1 billion in 2020.

Why artificial intelligence matters

AI adoption has stemmed from the technology’s wide range of benefits. Artificial intelligence and machine learning enable organisations to:

In addition to artificial intelligence improving how businesses operate, AI can also provide access to unprecedented amounts of data.

Delivering business value

Automation delivers consistency, speed and scalability to business processes. When scaled appropriately, studies have shown how companies can see up to three times the return on AI investment.

Providing competitive advantage

Machine learning and deep learning can enable companies of all sizes to not only gain access to massive amounts of data but also learn from it without a significant increase in investment.

The AI tools business leaders are investing in

Research carried out by McKinsey & Company showcases the main business functions in which organisations adopt artificial intelligence:

Within these functions, AI implementation could involve the use of smart virtual data rooms (VDRs), software solutions for product pivoting or the likes of customer service tools, such as chatbots.

VDR platforms in particular are utilising AI and machine learning to help run deals of all sizes even more efficiently. For the past few years, Drooms has deployed AI-based technology that is being used to analyse and filter content so that expert professionals can sift through and appraise vast quantities of data much more quickly.

What does the future hold?

There is no denying the power of artificial intelligence and its ability to generate insights and provide strategic leverage. AI, although in its early stages, is rapidly becoming one of the most widespread general-purpose technologies in human history.

Artificial intelligence will continue to change the nature of work and how businesses operate. It’s applications will keep expanding according to estimates by McKinsey who cite the most advanced deep learning techniques deploying things like artificial neural networks could create $3.5 trillion to $5.8 trillion in annual value.

Although AI can achieve impressive results in specific use cases, this will not displace professional expertise. The work done by humans is far more complex than the technology and more specifically machines can handle.

With emerging technologies like AI, there’s an incredibly broad set and a huge volume of material that needs to be reviewed. There are also many tasks and roles. Where there is repetitive and mundane work that needs to be done with a high degree of accuracy, currently businesses can identify use cases for AI that enable people to exercise judgement and draw on their experience. The effective digitisation and collection of material will be important for the current and future development of systems.

What to take into account

Paying attention to AI’s adaptation is more important than ever as businesses become more confident in leveraging the technology. The main issues surrounding artificial intelligence involve:

Furthermore, current adoption trends are variable across the globe creating difficulties with innovation and competition. The future of AI and the future of work will depend on how companies rise to such challenges. Organisations should make sure their individual AI adaptation is even across different business operations and ensure a technology enabled workforce through effective training and development schemes. Practitioners should also adopt a principles-based approach that would consider ethical codes and protocols.


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