Artificial intelligence is becoming less of a futuristic technology and a more integral aspect of today’s business landscape.
The usage of AI across the business universe is revolutionizing every industry, and Gartner reports that at least 75% of organizations use deep neural networks today.
In financial departments, AI is automating menial tasks and reducing errors in traditional manual workflows.
AI’s unfounded fears
There’s no doubt that businesses utilizing the right AI for the right reasons are seeing exponential benefits. Unfortunately, not every business unit is as excited about the available AI solutions that finance departments are gifted with. Change management is a significant component of failure when implementing any transformative technology.
Many humans still have unfounded fears about it gaining sentience or replacing them, and workers are wary of becoming obsolete once their daily tasks are automated.
But that’s never been the point of AI, machine learning, and automation because they augment human intelligence.
Humans are still very necessary
Take OpenAI’s GPT-3 and Dall-E 2 text- and image-generating models for example. Although they can generate a 1,000-word blog post with images within seconds, there could be a lot of legal liability issues if you were to publish raw content generated by one of these models directly on your website.
The content is never 100% accurate; human interaction is still essential to train, implement, and use AI across the business.
Simplifying AI for the average worker
AI data sets and outputs need to remain accessible, and making them accessible means tapping into everyone throughout the organization to apply their professional judgment to the data sets. This provides the machine’s velocity, variety, and veracity as it learns.
AI in financial departments
AI’s use in financial departments is so successful because payroll, compliance, accounting, taxes, etc., is complicated — especially when you’re a multinational corporation or utilizing the remote global workforce unlocked by the pandemic.
Expansive data sets
But you can import expansive data sets into AI to make it more useful. Streamlining all of this and optimizing processes not only reduces errors, but it frees up human workers to perform more advanced analytics that are closer to the reason they got into the industry in the first place.
How simplifying AI can open up usage possibilities
Simplifying AI for the average worker means they can focus on less menial, more innovative tasks and accomplish much more in less time.
GPT-3 and Dall-E 2 may not have flawless, production-ready outputs, but they utilize neural networks on large datasets of about 175 billion parameters across 45TB of text data. As a result, they’re perfect for ideation and conceptual work to get a firm visual image of the final product to work from.
Pass it around
Although their outputs seem wildly different (text versus images), both of OpenAI’s creations work similarly. While it seems like AI leads to faster advancements, what really happens is we discover one important concept that opens the door to new possibilities.
This is why getting the technology in as many hands as possible is important to see how others find use in the outputs it creates.
How AI brings more value to a business
As the quality of content-generating AI debate rages in the media and online forums, the technology’s uses for internal business functions are even more remarkable.
New ways of looking at things — skilled data scientists
AI across the business continues to open new ways of looking at things and allows skilled data scientists to develop complex models to predict anything you need to know — from machine health to possible market conditions and forecasting.
AI across the business can and will go beyond personal assistants, voice-to-text, and personalized recommendations to bring value to the roles of individual employees.
Better use of time
Leveraging specific AI technologies throughout the business keeps human workers at every level working only on tasks that cannot be automated. This includes processing exceptions to the rules (which there will always be), analyzing AI-generated outputs, and more.
Instead of spending our days manually putting together reports, we will be analyzing pre-generated reports and making advanced intelligent decisions.
Embracing artificial intelligence
When GPT-3 and Dall-E 2 were released, both writers and designers feared for their jobs. However, those fears were relieved as they tested the tools and got more comfortable with them. These tools can generate amazing work to assist writers and designers, but it still requires skill to understand how to prompt it for the desired results.
A professional can edit and polish it throughout the process in a variety of ways that will always require human instinct.
And an experienced photographer or graphic designer will get higher-quality outputs and know how to fix them in posts.
Focusing on higher priorities
Familiarizing yourself with these types of tools helps to better understand what they’re truly capable of and how they can be implemented into existing workflows while seeking better, faster, and more optimized ways to do things. That’s how finance departments leveraged AI to accomplish the most laborious and error-prone aspects of their jobs so they can focus on more important things.
And it won’t be long before AI transforms every aspect of every business.
Featured Image Credit: Sergey Zolkin; Unsplash; Provided by the Author; Thank you!