UNPACKING THE AI BUZZ: MAKING TECHNOLOGY MORE APPROACHABLE FOR YOU AND YOUR BUSINESS
Written by Jessica Murray
The AI buzz
It’s no secret that automation and AI are on the minds of business leaders. There’s so much innovation happening, it’s moving fast and there’s an intense feeling of FOMO in the air.
It’s exciting to think about the potential new technologies and AI-enabled platforms can deliver for businesses. On the other hand, it can be jarring because new tools and use cases pop up daily, making it daunting and hard to keep up, whether you’re very new to technology or not.
Since this is a big topic, I’m not going to cram all of my thoughts on how to guide you through getting comfortable with and using AI in a single post. This week will be an overview and tips to get started, while next week you can expect a useful framework for evaluating whether AI and automation are well suited for your business right now.
Breaking down key AI terminology
A lot of terms are thrown around with AI, which may not be familiar if you don’t work in the technology industry. Before a deep discussion on AI for businesses, we should set a common understanding of key terms.
In the spirit of being a user of AI, I prompted Perplexity to produce the following definitions of key terms you probably hear associated with AI.
AI: AI, or artificial intelligence, is the development of computer systems capable of performing tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and problem-solving.
Generative AI: A type of artificial intelligence that can create new content, such as text, images, music or code, by learning patterns from existing data and using that knowledge to produce original outputs.
Machine learning: A subset of AI that focuses on the ability of systems to learn and improve from experience without being explicitly programmed.
Natural language processing: A branch of AI that focuses on the interaction between computers and human language, enabling machines to understand, interpret and generate human language.
Prompting: The process of crafting specific instructions or queries to guide an AI system in generating desired outputs or performing tasks effectively.
Chatbots: AI-powered programs that simulate conversations with human users (e.g., ChatGPT).
Training data: The initial dataset used to teach an AI system how to perform its intended function.
Why AI matters
Now that we’ve established a common language, you’ll probably want to know what all the fuss is about. There’s been an outpouring of AI investment in the past couple of years, and it’s hard for a day to go by when there isn’t news about another company testing AI applications.
Here are a handful of reasons why the promise of its capabilities excites both individuals and companies.
Increased productivity: The ability to automate repetitive tasks at scale provides the opportunity for more focus on strategic work.
Speed to decisions: AI can rapidly process data and recognize patterns, which helps augment problem-solving and decision-making processes. People and companies can operate more quickly.
Cost efficiency: When AI drives more productivity, there’s the potential for significant operational and labor cost savings for companies.
Accessibility: Applications like ChatGPT make it easier than ever for individuals and small businesses to access advanced technologies.
Personalization: Customers crave personalization, and companies strive to efficiently deliver. This becomes easier with AI, given its data processing and pattern recognition capabilities. It can analyze vast amounts of input and decide how different customers should be served at scale simultaneously.
Excitement about the future: While the true impact of AI use cases is still unfolding and being tested, there’s a sense of thrill that we are on the edge of transformative change for society.
Practical steps to getting started with AI
Given the potential benefits, business owners must become increasingly familiar with AI and its applications. However, that doesn’t mean AI will be appropriate for every business today. Careful consideration before diving into the AI deep end for your business’s operations is crucial to implementing technology that will work with your business, not against it.
For readers who haven’t scratched the surface yet, there are several ways to get more acquainted with AI and how it can be used.
AI news: Follow newsletters and thought leaders to stay up-to-date on innovation (e.g., Ben’s Bites).
Test AI tools: Get free accounts on platforms like ChatGPT, Claude and Perplexity and start testing. Using AI first for personal use cases makes it fun, lowers the pressure and helps you think creatively about how to apply the technology.
Review existing technology: What technology do you use in your business today? See if the platforms offer AI-enabled features and read up on the capabilities.
Learn AI fundamentals: Take an online course or take advantage of free tutorials.
Consult experts: Consider partnering with a third party, like Empower, who can help you assess your operations and walk you through potential options.
I’m doubling down on bullet point #2 because it’s an important point if AI feels intimidating. Testing AI in low-stakes scenarios can demystify the technology.
Here are ways I’ve used ChatGPT for personal use:
Building an itinerary for an upcoming international trip.
Editing an email before sending it.
Summarizing a book on potty training to prepare for that phase of parenthood.
Telling jokes or writing a funny poem.
Researching the best places to travel around the world in the fall.
Explaining a complex topic like I’m a five-year-old.
Spending a little bit of time each day testing and reading about AI makes a big difference in your understanding of how it works and can apply to your business.
Be informed: AI risks and limitations
As much as AI is exciting and provides benefits, it’s not without pitfalls. Keeping the following, and more, in mind as you explore AI will help you better understand both its power and limitations.
Hallucinations: AI models can produce false or misleading results, which aren’t always easy to detect. There can be an overreliance on the AI model outputs, thereby potentially spreading misinformation. It’s important to cross-reference facts and to prompt for sources of information.
Garbage in, garbage out: Bad data in means bad data out. You can't expect accurate outputs if AI models aren’t fed quality inputs. Strong data quality and ongoing data management are key to getting value out of the technology.
Unrealistic expectations: There’s a tendency to over-rely on AI model outputs and think of AI-powered solutions as a cure-all to problems. Doing so could lead to overestimating the return on investment and underestimating the resources required to integrate the technology into workflows, train staff, etc.
Lack of transparency: Many AI models operate as a “black box,” meaning we don’t know exactly how they work and calculate the outputs. This can make it challenging to explain decisions made, or augmented, by AI.
Data privacy and security: This is a big topic in this space. Feeding AI models with prompts and data without understanding how the data is being processed and used, the platform’s level of security, etc. can lead to issues with sensitive data being leaked, breached or improperly handled.
Once you become more familiar with AI, how it works, understand risks and test your basic prompting skills, you’ll be in a stronger position to evaluate how to harness it for your business.
Next week: how to approach AI for your business
We’ve covered a lot today so the evaluation process will be our topic for next week!
Hint: It all starts with understanding your business problem first, then searching for solutions.