ChatGPT has attracted an enormous amount of excitement, experimentation, and investment.

According to a Fishbowl survey, nearly a third of professionals have used ChatGPT or another AI program in their work. The Stanford Daily says “scores” of Stanford students used ChatGPT on final exams. And tech media outlet CNET is employing ChatGPT to write stories. 

Microsoft just announced a multi-year, multibillion-dollar investment in OpenAI, deepening its partnership with the ChatGPT creator as it works to advance its search efforts. With this, Microsoft is making a significant bet that the interface between humans and computers will evolve.

ChatGPT is the highest-profile example of generative AI. But it’s just one example of this modality of AI that is used to create net new content. Alphabet’s DeepMind is another example. 

The generative AI space, which has captured the imagination of the venture capital community, also includes much smaller companies. VCs are looking for something new to drive momentum and to take the focus off the big-short failings in crypto and some of the bloated software-as-a-service valuations. Generative AI appears to be that bright shiny object. 

As Insider reports, Jasper and Runway are among the generative AI companies that have raised “eyeball-popping amounts in the past year” despite a lousy year for VC investments.

Generative AI will level up requirements for internet content quality, providing consumers with higher-quality experiences. But generative AI will put pressure on content creators. 

If content creators don’t produce content as good as or better than what generative AI can create, they won’t be able to compete. However, generative AI provides content creators with an easy-to-use toolkit to outsource tasks they don’t enjoy so they can do more fulfilling work. Generative AI can also do top-of-the-funnel work to orient what to talk about or write about.

Despite generative AI’s strengths, it has some shortcomings. Right now, these models crawl the internet for information. So all of the inherently biased, flawed, and incorrect data floating around the internet is baked into its data sets. That differs from software business automation, which relies on specific enterprise data inputs and predefined rulesets. 

What does all this mean for your business? And how can you move forward with automation to become more operationally efficient and withstand the test of time as competitors modernize?

Assess whether your public-facing functions could benefit from generative AI.

Generative AI is not currently a match for enterprise back-office automation. But existing business process automation technologies provide the opportunity to improve significantly the efficiency and productivity of your back-office operations and drive business success.

However, you want to leverage generative AI for your business. In that case, you may explore public-facing functions such as marketing, public relations, and sales, for which generative AI may be helpful. Generative AI can also help with product ideation.

Down the road, GPT-4 and what follows will be orders of magnitude more significant in terms of the data points informing the model. And many of these models that have been trained and gotten pretty far based on broad, high-volume data sets could potentially bring in private data sets. But it will take about five years until valuable personal data sets are appropriately organized, and the models become good enough to enable AI to address interesting core business operations.

Use business-specific process automation technology to improve your operations.

Over time, we’ll see companies use private data sets to leverage new models and create the next iteration of AI. We’re working on this ourselves. But generative AI is unlikely to help automate day-to-day business operations soon. The data sets on which software business automation relies typically aren’t centralized, and even if they are, they’re not public. 

While generative AI isn’t beneficial in most of your data-to-day operations for an extended period, services and technologies make it easy to automate and continue improving the efficacy, efficiency, and throughput of your back-office processes.

Consider what areas of your business might benefit from business process automation-specific technologies. For example, in today’s economic environment, you might want to leverage intelligent bots to enable business process automation to do more with less or reduce your costs. Perhaps your goal is to increase data processing times or improve data quality integrity. Or maybe your current teams are struggling to handle back-office operations work either generally or seasonally, and you are considering using intelligent bots to ensure business continuity. Business process automation, powered by intelligent bots, can enable you to do any or all of those things.

Get started with automation now to remain competitive today and tomorrow.

Most competitive companies adopt software-based automation to handle repetitive, rules-based back-office work. For example, business software automation is making big waves in the healthcare, real estate, financial services, and insurance sectors. And a growing number of accounting and legal departments within businesses of all stripes are benefitting from the power of intelligent bots. 

Avoid falling behind the competition by getting started on your transformation.

Generative AI is excellent. However, it’s not yet ready for most business use cases. 

But you can leverage business automation to improve your organization today.

‍Dan Parsons is co-founder and chief platform officer of Thoughtful, whose mission is to accelerate the world’s adoption of automation and AI so humans can solve our most complex, existential problems. Thoughtful creates and manages software intelligent bots that supercharge customers' operations across all primary business functions, including healthcare, revenue cycle, finance, legal, HR, IT, and beyond. Dan’s responsibilities include crafting and executing the product vision, strategic corporate development, and building a world-class go-to-market team. Dan has over 13 years of experience as an operator and product leader (a two-time former founder). His career has been staked in leading startups such as ORA Interactive, DRYV, and BetterUp to build incredible products to fuel growth and ROI. Dan graduated from the University of Cincinnati with a finance and information systems degree. Dan lives in Cincinnati with his wife and two sons, and outside of work, he enjoys spending time with family, live music, reading, Web3, and learning about new schools of thought.