Beyond the Hype: Unlocking Real Business Value With Gen AI

As Gen AI investments increase, businesses must consider if it is the type of AI they need, or if it is just one part of the digital transformation puzzle

The generative AI (Gen AI) space only continues to grow.

Just yesterday (13th May 2024), leading AI company and ChatGPT creator OpenAI unveiled GPT-4o - its latest multimodal AI model that boasts faster response times and improves on capabilities across text, voice and vision. 

The new model can also translate speech between 50 languages and is designed to perceive emotional cues from users.

OpenAI is just one example of a company that has rapidly developed and updated its Gen AI capabilities. Competitors Anthropic and Google have also been quick off the mark to introduce the latest iterations of their AI and Gen AI models designed for both enterprise and personal use.

However, whilst the potential of Gen AI is remarkable, it is important that businesses keen to invest in the technology are considering all aspects of the technology - including how to handle and manage the power of it.

Creating a stronger AI

AI experts have been quick to advise that investing unnecessarily in the technology could cause more harm than good. A recent article by Gartner cites that misusing Gen AI could result in unintended negative consequences for a business - especially if they do not invest wisely.

Image: Gartner

Gartner cites that over-focusing on Gen AI investments could lead to a company ignoring alternative digital transformation strategies and other AI techniques that could be a better fit for their organisations.

Likewise, Gartner suggests that the Gen AI hype could lead to project failures, as businesses may be so keen to implement the technology, it makes operations more complex.

Gen AI is also not the sole solution. It can also work in tandem with other AI techniques in a wide variety of different combinations to deliver greater performance and transparency. Harnessing Gen AI with other techniques could also result in lesser costs, which is an attractive proposal for businesses during a time of immense energy demands.

Some Gen AI combinations (as cited by Gartner)
  • Non-generative machine learning and Gen AI models
  • Optimisation search and Gen AI models
  • Simulation and Gen AI models
  • Rule-based systems and Gen AI models

Combining capabilities in this way serves to make the AI use cases more powerful. More robust systems create an AI that is more responsible, reliable and can propel a company towards greater successes.

Keeping strategy safe

Trialling simpler AI systems prior to investing fully into Gen AI could be a positive strategic move for businesses. This is because the more simplistic techniques are often less expensive and easier to understand for an organisation learning about AI perhaps for the first time.

Likewise, simpler AI means less room for risk, so if something goes wrong it can easily be fixed.

In a world where AI is beginning to dominate the business landscape, there are numerous organisations investing in a technology they may not fully understand yet. AI experts are therefore encouraging business leaders to educate themselves and their workforces before jumping in the deep end.

"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,” highlights Kshitij Jain, EMEA Practice Head & Global Chief Strategy Officer, Analytics at EXL.

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