AI is penetrating further into the business environment every year, forming a solid foundation for increased adoption. McKinsey finds that companies that are making greater investments in AI are seeing greater financial returns. As a result, more businesses are scaling up their investments to speed AI development.
Rapid AI Adoption
Higher ROI and improved competitiveness, together with greater digital maturity, have boosted AI adoption. For example, according to IBM findings, 53% of IT professionals have accelerated their rollout of AI over the past two years, which is 10% more than in 2021, when the trend was fueled by the COVID-19 pandemic.
As a result of wider AI adoption, experts expect the global AI market size to grow rapidly, with some predicting a CAGR of 37% between 2023 and 2030.
But should we consider AI more like a tool to be employed by skilled users, or more like an employee who can perform various roles within a business?
AI As Employee: Use Cases for Businesses
Here are some popular AI use cases I'm seeing in 2023.
1. Automation
According to McKinsey, robotic process automation (RPA), which allows businesses to optimize service operations, remains the most common application of AI. Improved scheduling, streamlined processes and automated repetitive tasks are just some AI implementations commonly used to improve the employee and customer experience.
For example, AI can significantly reduce the workload in telecommunications service centers. If in the past a customer had to contact support to have their accrued roaming charges adjusted manually, this now can be delegated to a trained model. AI can detect roaming status, track usage and automatically apply the optimal roaming package to minimize the customer's bill.
2. Text and Image Generation
AI is generating content at an increasing level of quality, which has led businesses to double the number of AI capabilities they use between 2018 and 2022. As of December 2022, businesses ranked natural-language text understanding as the third most common use case, and that was prior to the emergence of more advanced generative models like ChatGPT.
• Graphical content generation: AI can create realistic images from textual descriptions, and even generate NFTs based on the work of famous artists. Examples include DALL-E 2 and Midjourney, which require textual explanations of what should be created and can adjust the image based on your edits.
• Text content generation: Similarly, AI models based on GPT-3 can generate text content. One recent offering, ChatGPT, which received 1.8 billion visits in April 2023, can write text content regardless of topic and style. To get a text summary, article or even translation, you simply type out a specific request and the conversational bot will quickly deliver the output.
Besides this, ChatGPT is trained to generate simple code. This tech does need to be updated as it's only trained to use pre-2021 data. Nonetheless, it is already being embedded in Microsoft Word, Excel and Bing.
3. Virtual Help
AI has become an always-available virtual assistant that can serve as a customer support chatbot, a virtual therapist or simply a friend. ChatOwl, a company that plans to offer users virtual therapy, has just raised $1.1 million in funding. Several other companies are also developing AI friends or companions, like Replica and Chai Chat.
4. Decision Support
Businesses keep accelerating decision-making to become more resilient, and now AI can assist with that process. According to Gartner, demand/revenue forecasting, decision support and POC revenue forecasting are among the top five AI use cases in corporate finance in terms of business value and feasibility.
By leveraging large piles of data, AI and ML prediction algorithms identify trends and apply them to forecast possible future outcomes. They can also predict the impact of a decision taken when relying on hypothetical data for accurate, data-based decision-making.
The Verdict: Tool or Employee?
I believe AI has already passed the stage of being useful tech that helps businesses stay competitive. With its recent advancements in data processing and content generation, it can be treated more like an employee and trusted to perform simple yet meaningful tasks.
Whether your company needs a junior developer like ChatGPT, an author or content manager like Neuraltext or Textio, a personal assistant to take notes like Fireflies or to convert text to voice like Murf, or a legal advisor like Legal Robot, you can now delegate at least some simple tasks to AI. This allows humans to address more important tasks.
But instead of deciding who to hire—AI or a human being—it's best to look for both and recruit new talent with deep AI professional background. While experts emphasize a rising demand for such specialists and a talent shortage, the efforts are worth it: you will benefit from both an experienced employee and AI innovations.
To source developers with a proven professional AI background, consider delegating the project to a reliable vendor with relevant expertise. (Full disclosure: My company is one such vendor, but you have many options in this space.) This can save on recruiting costs, allow you to start innovating without spending many months on hiring and promote innovation across the industry through professional collaboration.
Final Thoughts
Despite the increasing number of AI-driven tools, I believe businesses should focus on hiring AI-competent specialists. While such an approach requires more effort, it allows for a better output as skilled specialists can train an AI model to make sure solutions will be tailored to your business needs.
