Ensuring that AI leads to Meaningful Impact for Businesses

With EXL insights, we explore how AI holds great transformative potential, but its success relies on clear business objectives and responsible deployment

AI will continue to transform global enterprises - but only with the right approach.

Over the past year, the world has seen the ground-breaking impact caused by AI technologies. However, there has been much discussion throughout the global business landscape about ‘developing for the sake of developing’ and questions over how AI could impact workforces if not harnessed safely or efficiently.

Whilst plenty of organisations around the world are keen to invest in AI, oftentimes they do not have clear objectives as to how AI could look within their company. With an obvious strategy, there is real potential for businesses to achieve successful digital transformation.

AI: Giving businesses an edge

It has already been established that AI has the power to transform key industries, from optimising existing operations, to allowing human workforces to progress faster with more specialised tasks.

As a result, businesses are able to achieve greater scalability, as organisations can focus on improving challenges such as scalability and customer experience - allowing them to have an edge and perform better in a very competitive digital landscape

Given that AI has already increased productivity across a number of industries, from generative AI (Gen AI) in marketing to advanced analytics and machine learning in supply chains, driving productivity and efficiency gains. However, there is potential for it to be leveraged even further still, allowing it to be more embedded into a business.

AI technologies have already become essential tools for businesses looking to thrive in the digital marketplace. However, just as there are opportunities, there are also threats - which attests to the importance of embedding AI technology safely and securely in order to eliminate risks and increase successes.

Enterprises facing increased digital pressures

A recent EXL survey found that 86% of financial services leaders reported that their firms are investing upwards of £7.9m (US$9.9m) in their most recently completed fiscal year. Likewise, 35% reported investments of £39m (US$49.2m) or more.

However, in order to have a meaningful impact, EXL states that firms must prioritise data optimisation. Prioritising data architecture, quality and governance will ultimately lead to enterprise AI having greater impact.

Enterprise anxieties over AI remain though, according to EXL, which states that nearly three-quarters of senior executives they surveyed claim to be concerned about the use of generative AI (Gen AI) in the workplace. In fact, they have cited fears such as Gen AI ruining brand or company reputation, the technology learning to operate autonomously and the possibility of it reporting inaccurate data.

Such rapid advancements in GenAI have captured the attention of governments worldwide, with many organisations eager to leverage the power of this technology to address complex challenges and improve public services.

However, this inevitably comes with challenges for businesses. In order to effectively implement responsible AI technology, organisations would do well to consider risk management in line with their digital transformation strategies. 

Kshitij Jain, EMEA Practice Head & Global Chief Strategy Officer, Analytics at EXL, says: “Our findings demonstrate that industry leaders recognise the transformative potential of AI for their businesses, but it’s also clear that they are under significant external pressure to implement the technology – especially while competition is hot and new solutions are being developed all the time.

“The risk is that this mounting pressure can lead to investment that isn’t properly thought through. A need to move quickly can mean ensuring operations are truly data driven and gets de-prioritised, and this can be a costly mistake. The outputs and impact of AI are greatly enhanced when implemented within an organisation which puts data architecture, quality, and governance at the top of the list.”


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