As businesses continue their journey to the cloud, organizations find it difficult to recruit – and pay – for architects, engineers and developers with the right skillset. According to an IDC survey, 90% of enterprises will be affected by IT skills shortages by 2025. The lack of access to resources and inherent cost is one of the top obstacles preventing organizations from transforming their business and seizing digital opportunities.
The widespread multi-cloud environment is adding complexity to the digital business model, and integrations between a core platform and business applications call for a set of specialized experts in various cloud platforms, SaaS solutions, IoT and so on. This makes the skills gap even wider.
What to do?
Scale through Generative AI
This is where Generative AI comes in.
Generative AI has been the talk of the town since OpenAI launched ChatGPT. The use cases have been both inspiring and alarming. From my perspective one of the most interesting takeaways is the use of Generative AI to write code. And not just write code but automate much of the coding and collaboration process in such a way that the AI can suggest several lines of code for the developer to modify or approve, thereby boosting both developer and business productivity. For the same reason, people in the software industry compare the impact of Generative AI for software development to that of the emerging Internet in the 1990’s.
Today, businesses are either forced to pay extra for internal or external developers to get a digital project done – or simply postpone or cancel the project. My prediction is that Generative AI will be able to help businesses who are not able to find and recruit the needed software resources on the global developer market.
Generative AI can be trained to scale the developers and automate tasks needed for managing a multi-cloud environment. However, as we have already seen and heard, the new AI models are not perfect. Answers from Generative AI can’t be trusted without humans interfering in the design and approval process. The new relationship between “man and machine” can be defined as a monitored quality assurance collaboration where the AI quickly performs the first draft of a task, and then the software developer goes through the code and makes sure that everything is okay.
This is a major change. It will affect companies’ search for talent, ease the pressure on internal IT resources and accelerate digital transformation. One good developer can now do what not so long ago was the work of many, and people who have never programmed will soon be able to create workable code.
Early adopters are getting ahead
Critics might say that what I’m describing is a future scenario. That the maturity of Generative AI does not suggest that they are ready to be implemented. I disagree. Research studies from, among others, GitHub show massive increases in speed when writing code. The technology is ready to be deployed in businesses all over the world, and early adopters have much to gain.
What is left to be clarified though is the adoption of these new AI models in a business and technology blueprint. Generative AI is such a powerful tool that regulation and guardrails are a prerequisite to drive business value. A preliminary impact assessment must be carried out to make sure that you know what you are unleashing, and the AI model must be trained according to your data ethics, business policies and other parameters that fit your company’s business strategy and core values.
For inspiration, we use different frameworks for implementing Generative AI in a business context in Deloitte. For instance, we have a framework for managing risks and limitations associated with Generative AI – the Deloitte Technology Trust Ethics (TTE) framework – which can be leveraged to build, deploy and commercialize AI use cases. The framework supports a holistic approach to emerging tech and include thoughts on responsibility, accountability, reliability and potential bias. Earlier this year, Deloitte also launched a Generative AI Practice. It’s a concept that brings together Deloitte’s deep industry experience, skilled AI engineers, and ecosystem and alliance partners to build Generative AI use cases that accelerate the pace of business innovation.
Regardless of your preferred way forward, Generative AI is here, ready to assist you and your developers and close a skills gap that threatens to undermine your business model.
