The Gist
- AI's great, but ... Artificial intelligence (AI) is a promising and useful tool for businesses, but it should be viewed as an augmentation for people, not a replacement for them.
- Start me up, AI. AI can be a great starting point for strategic plans, but it should not be relied on to complete them.
- Just be transparent. AI can analyze large amounts of data that humans cannot, but it is important to strive for transparency in AI models to avoid introducing bias.
Working in the marketing technology space for over a couple decades now, I’ve heard a lot of buzzwords over the years. Some of them were warranted, some not so much. Some of them too far ahead of their time, and some of them hitting at just the perfect time.
I won’t even pretend to think that, as you’re reading this, you haven’t heard anything about ChatGPT, and at least some of the buzz around artificial intelligence (AI) based tools these days. It would be easy to dismiss it as just the latest in a series of buzzy things that will run their course. While there is plenty of hyperbole, in this case, however, I urge you to pay closer attention.
With AI tools, it would be best to focus less on a specific application. Much as many might be saying, ChatGPT is neither the end nor the beginning of anything. But it is a really promising and useful tool. So are many other AI-based applications that are changing the way companies think about they work and serve their customers.
In this article, I’m not going to focus on specific AI tools, but instead talk about the mindset shift you and your team should have as you either slowly or quickly embrace artificial intelligence in your work. We’ll discuss four ways to do this. Let’s get started.
When It Comes to AI, Augment, Don’t Replace
First, a good way of thinking about artificial intelligence in general is that it is best utilized as augmentation for people and not as a replacement for them. After all, what percentage of your teams’ work on average is monotonous and could conceivably be automated? According to a recent survey by UiPath, 67% of workers in the United States feel that much of their workday is spent with tasks that could easily be automated. Additionally, according to Harvard Business Review, workplace monotony can have a direct impact on employee morale, quality of work and performance.
Thus, there is a lot of opportunity here: Employees want to be freed up from monotonous, repetitive tasks, and doing so with AI-based tools can allow teams to focus on more valuable, strategic work. This could include innovations that improve the customer experience, save the company money, or bring in new sources of revenue. All while AI is taking care of the drudgery. It’s a win-win!
Related Article: How AI-Driven Data Enhances CX
The AI Path: Start, Don’t Finish
Second, a good way to approach utilizing artificial intelligence in your teams’ work is that it can be a great starting point, but should not be depended upon to complete a strategic brief plan — or anything else.
For instance, ChatGPT and other generative AI tools offer great starting points. By asking a series of questions you can get some basic ideas and information on which to build a report, an article or other more strategic outputs. This is utilizing technology so that every party is playing to their strengths. For all our benefits, humans often have a hard time starting things, as evidenced by our tendency to procrastinate. This reluctance to start can be negated by utilizing AI tools to give us something to build out instead of staring at a blank screen waiting for inspiration to come.
Thus, thinking of AI as your starting point, and your strategic human teammates as the closers, can help to frame some more successful adoption of artificial intelligence in your organization.
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AI Adoption: Curate, Don’t Summarize
Another way to think about adopting AI into your work is that it can be a great curator of information for you and your teams. That said, although tools like ChatGPT and others have the capability to find information and summarize it from across the Web, there are some fairly serious downsides to this approach.
For one, it can often be difficult to determine exactly from where some of the information is being summarized. It may be from a less-than-reputable source, or it may be from an edge case that is not fully representative of the information you are attempting to summarize. Additionally, there can be elements of bias that are difficult to detect and protect against if you are relying on AI to simply scour the web for any and all information on a topic.
Thus, you can use AI-based technologies to curate a wealth of information that humans can then review and ensure meet the standards and focus for which you are looking. This leverages the strength of AI to scour large troves of information while leaving the humans to making high-level judgments about what is appropriate and what is not.
AI Aim: Analyze, Don’t Strategize
Finally, in addition to the ability for AI to help with the curation of information from across vast data sets, AI-based technologies like machine learning, deep learning and natural language processing (NLP) can help you and your teams analyze large amounts of data that humans simply could not in any reasonable manner. This can be a building block as you bring in your human team to take that analysis by AI and build strategies and plans that benefit from AI’s ability to parse vast amounts of structured and unstructured data.
Similar to what was mentioned under curation, don’t underestimate the ability for bias to be introduced into a machine learning algorithm. Strive for transparency in your AI models so that bias can be rooted out, and your team’s strategies can be based on the best possible combination of machine and human intelligence.
When teams approach AI in a realistic manner, utilizing the three approaches described above, they can have an incredible amount of success while retaining the strategic control that humans are simply better at wielding.
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