Generative AI has cemented its role as more than just a technological marvel. Other than it shaping the future of enterprise, it’s quickly evolving into an integral part of our society – where people and machines work in synergy.
As the fabric of enterprises around the globe, GenAI’s influence is set to grow.
Which is, according to Gartner, very much akin to the impact brought about by industrial advances such as the steam engine, electricity, and the internet.
We took a look at one of Gartner’s insightful articles on the impact of GenAI on enterprises. And we found some very interesting tidbits.
What is Generative AI?
Generative AI leverages pre-existing artefacts to create new, authentic ones without repeating the training data.
Wait. What?
Simply put, generative AI uses old information to make new and unique things.
And the use cases are pretty out of this world. It can create pictures, songs, text, videos, software, and even product designs in a fraction of the time it would take concerted human effort.
These AI models essentially work with complex maths and huge amounts of computer power to predict what comes next in these given tasks.
People use Generative AI to:
- Make content by simply asking for it in normal language.
- Create new things in areas like medicine, computer chip design, and material science.
- Improve processes and overall output across different business functions (marketing, HR, operations, etc.).
GenAI: A Revolution in Business Value
Gartner categorises the potential of Generative AI in terms of revenue, cost, and risk opportunities.
Revenue
Generative AI speeds up the creation of new products and opens new revenue channels.
“Generative AI will enable enterprises to create new products more quickly. These may include new drugs, less toxic household cleaners, novel flavours and fragrances, new alloys, and faster and better diagnoses”.
Enterprises with a higher AI maturity level will see greater revenue benefits.
Cost and Productivity
This incredible technology can augment workers’ capabilities, optimise long-term talent, and improve workflows.
“Generative AI can augment workers’ ability to draft and edit text, images and other media. It can also summarise, simplify and classify content; generate, translate and verify software code; and improve chatbot performance. At this stage, the technology is highly proficient at creating a wide range of artefacts quickly and at scale”.
By generating a wide range of artefacts swiftly and at scale, it enhances productivity.
Risk Management
Generative AI aids risk mitigation by providing broader and deeper visibility into data for quicker identification of potential risks.
It also aids in complying with sustainability regulations, mitigating the risk of stranded assets, and integrating sustainability into decision-making processes.
Generative AI’s Impact Across Industries
GenAI is slated to significantly impact sectors such as: pharmaceuticals, manufacturing, media, architecture, interior design, engineering, automotive, aerospace, defence, medical, electronics, and energy.
For instance, by 2025, over 30% of new drugs and materials could be systematically discovered using generative AI techniques.
Also, generative design could optimise the design process by producing an array of potential solutions for engineers in industries like manufacturing, automotive, aerospace, and defence.
Best Practices and Risks
Adopting Generative AI isn’t without risks. You’ve got:
- Lack of transparency
- Inaccuracy
- Bias
- IP and copyright issues
- Cybersecurity and fraud
- Sustainability concerns
Companies are advised to prize transparency, conduct due diligence, address privacy and security issues, and test extensively with internal stakeholders before venturing into customer-facing applications.
When it comes to costs, generative AI ranges from being practically free to costing millions, depending on the scale and requirements of the company.
Small to midsize enterprises could gain significant value from free versions or low-cost subscriptions of applications like ChatGPT. Larger enterprises desiring greater data analysis and security may need to invest in custom services.
Generative AI: The Future is Now
Gartner predicts a steady growth of generative AI’s impact on enterprises in the next five years.
By 2024, embedded conversational AI will feature in 40% of enterprise applications. By 2025, 30% of enterprises will have implemented an AI-augmented development and testing strategy.
Looking further ahead, by 2026, generative design AI will automate 60% of the design effort for new websites and mobile apps, and over 100 million humans will engage “robocolleagues” to contribute to their work.
By 2027, nearly 15% of new applications will be automatically generated by AI without human involvement.
In essence, generative AI stands as a paradigm shift, poised to revolutionise industries and business models, rendering them more efficient, productive, and innovative.
As Gartner notes, Generative AI isn’t just a technology — it’s an integral part of a society where humans and machines work harmoniously, pushing the boundaries of what’s possible.
*Want more AI content? Check out our blog for your daily dose of content!
