Artificial intelligence is booming. The technology is rapidly developing and the market is expected to grow exponentially. Estimates find generative AI is poised to explode, rising to over $1.3 trillion over the next 10 years from a market size of just $40 billion in 2022.
Many industries are already employing artificial intelligence tools. In particular, AI is already transforming the global business landscape, driving innovation and boosting productivity across various sectors.
If you’re studying a business-related degree, like an online MBA course, understanding the potential of artificial intelligence is crucial. Statistics show companies are already hiring for jobs related to generative AI skills, and the demand is only growing year over year.
This article explores a new study from CGI, the leading global IT and business consulting services firm. The firm researched how business leaders prioritise AI to drive innovation and efficiency.
The CGI study
CGI’s study into artificial intelligence featured more than 1,800 in-person interviews with executives, of which 80% were C-level. These interviews offered an in-depth look into the current business landscape and the role technology has in shaping its future.
According to CGI and their study, business leaders are pursuing a dual agenda, dubbed the ‘AND’ approach. This strategy consists of driving growth and innovation whilst also controlling costs and improving efficiency.
Key findings
The study focused primarily on UK businesses, with questions about their priorities, areas of growth, and the deployment of generative AI tools. Below, we’ve outlined the major key findings from the study.
- 87% of UK respondents in the study are already experimenting with generative AI.
- 32% of UK organisations are driving digitalisation as their top priority to achieve optimised and agile operations.
- 35% of businesses already rely on value delivered through AI and resilient data pathways.
The findings from CGI’s study aren’t just unique to the UK either. Globally, organisations in every sector from healthcare to the entertainment industry are looking for ways to implement AI to cut down on costs and increase efficiency.
For example, healthcare organisations are looking to employ the use of artificial intelligence to cut down administrative tasks and personalise treatment. This could reduce the risk of burnout for healthcare workers and increase patient health outcomes.
Photo by Tara Winstead on Pexels
AI statistics
Findings from the CGI study are consistent with the results from other sources of data, like the recent survey on AI from Salesforce. They questioned over 1,000 marketers on whether they’re planning to use or using generative artificial intelligence tools.
Over half of the respondents (51%) said they are already using or experimenting with AI in their workplace. Another 22% of the respondents said they are planning to use generative AI.
According to Salesforce, these were the most common uses of AI in the marketing industry:
- Basic content creation
- Copywriting
- Inspiration
- Analysing market data
- Generating image assets
The AND agenda
The ‘AND’ agenda refers to how business leaders are looking to simultaneously grow and drive innovation whilst cutting down costs and improving operation efficiency. Many digital leaders believe AI will play a massive role in this.
This dual focus on growth whilst managing costs isn’t just unique to the UK, either. Worldwide, business leaders are looking towards artificial intelligence tools to streamline operations, reduce overhead, and create new revenue streams.
Photo by ThisIsEngineering on Pexels
Challenges and the future
The rapid evolution of artificial intelligence and the use of generative tools aren’t without its challenges. Already, there have been many controversies surrounding the use of AI which has started discussions regarding safe AI use and ethical considerations.
One of the most prominent ethical issues regarding AI is the potential ramifications of discriminating and perpetuating biases. This is because if the data sets used to teach AI have biases, they’ll carry into the tool, too.
Artificial intelligence also has a ‘black box’ problem. This refers to when it is difficult to understand how a system, in this case AI, arrives at a decision. These systems are known as “black boxes” because they lack transparency.
Because of the lack of transparency, it becomes harder to hold artificial intelligence accountable and understand the way it works. It has also become one of the main challenges incorporating AI into the workplace faces.
Ethical considerations
Artificial intelligence, particularly generative tools, faces many challenges and ethical considerations before we see mainstream adoption, especially in high-risk settings. Because technology is evolving so rapidly, it will also take time for regulations and laws to catch up.
Australia already has voluntary guidelines for using AI in high-risk settings, which they have proposed to make mandatory. These mandatory ‘guardrails’ would ensure the safe and transparent use of artificial intelligence in high-risk settings, like healthcare.
Artificial intelligence is already contributing to global business growth, as companies begin to deploy AI tools to help streamline processes and increase productivity. Before AI use becomes mainstream it is important to consider the ethics and place guardrails before it is too late.
Particularly in business, the following ethical considerations need to be explored:
- Algorithmic bias: Algorithms are the backbone behind AI tools and machine learning. Whilst these tools can help with analysing data and streamlining business operations, AI can learn negative bias through the data sets they learn from. This can lead to discrimination and unequal access to resources.
- Cybersecurity: Cybersecurity is a major ethical concern for AI-driven firms, because depending on the setting, they handle sensitive data. Particularly in high-risk settings like healthcare, a data breach can be catastrophic, not only impacting the organisation but also for vulnerable patients.
- Data collection/privacy: Because artificial intelligence tools learn through data, there have been many discussions regarding data and privacy. This includes how the data is collected, consent, and how it is stored.
Artificial intelligence is already positioned to revolutionise industries, and it will, but experts will be required to ensure AI tools are used ethically and held accountable.
