How AI Is Transforming Businesses
By Michael Le
For the average person, it might seem that one day there wasn’t artificial intelligence (AI), and then suddenly it was everywhere. But the truth is, tech-enabled businesses have been leveraging AI for years to improve their business operations and user experience.
Small and mid-sized businesses and organizations are starting to catch on. Early adopters of AI marketing tools like ChatGPT, JasperAI, and Midjourney are impressed with their potential to supplement communications and customer support processes.
In this article, we’ll cover:
What Is AI and How Is It Used in Everyday Life?
Impact of AI on Business Operations
What Are AI Best Practices for Businesses?
This article is part of a larger Brandmint series on AI, geared toward keeping business and organization leaders informed on AI best practices. Subscribe to our newsletter MintMail to keep up with our blogs, marketing insights, and more!
What Is AI and How Is It Used in Everyday Life?
Artificial intelligence (AI) refers to the science of making intelligent machines or programs that can simulate human intelligence. AI uses machine learning algorithms to train on provided content, with some human input to condition the model. The AI’s responses are limited by its dataset (which it will synthesize, rework, and mirror) and its conditioning (human input).
Stronger AI models capable of deep learning can create digital neural networks composed of more than three layers of inputs and outputs. And natural language processing (NLP) technology further allows AI models to interpret and comprehend human language.
So what does this mean to the average person? Well, you can think of AI as a scalable learning model that can help achieve a specific task.
You’ve likely engaged with AI on a daily basis without even realizing. Ever use a search engine like Google or Bing? AI algorithms scour the internet and rank relevant resources to give you the top results. Or rely on tools like Grammarly to proofread your emails and adjust for tone? An AI model suggests those enhancements based on language rules, trends, and similar texts.
Spotify playlist recommendations, Netflix automatic thumbnails, up-to-date traffic insights on maps, your smart home assistant—all of it leverages AI to analyze human behaviors and deliver personalized results.
Impact of AI on Business Operations
Because of AI’s ability to spot patterns in data and understand text-based inputs, AI does well at data analysis and communications. Levering AI for business allows owners to potentially accomplish repetitive, templated tasks efficiently, while allowing the internal team to focus on more human-centric projects.
Recently, Forbes Advisor surveyed 600 business owners using or planning to use AI to augment their businesses. The following charts show how businesses use AI to improve internal processes as well as customer-related tasks.
Some key insights:
At least 1 in 2 surveyed businesses use AI to augment their production processes, process automation, and SEO-related tasks.
46% of surveyed businesses rely on AI to improve internal communications such as strategies, presentations, and reports.
About one in three businesses plan to leverage AI for website copy, idea generation, and even coding.
More key insights:
Over 50% of surveyed businesses are leveraging or plan to leverage AI for customer service support, cybersecurity support, and fraud management.
Nearly half of surveyed businesses are using AI to improve customer relationship management.
About one in three surveyed businesses rely on AI for inventory management, content production, and product recommendations.
Forbes’ report goes on to say that nearly two-thirds (64%) of surveyed businesses believe AI will improve customer relationships. This makes sense considering AI’s potential to anticipate human actions and wants based on patterned behaviors between similar customers.
What Are AI Best Practices for Businesses?
It might seem like AI is the magical solution to all of your problems, but business consulting experts are more cautious. When implementing AI for business, you need to make sure you’ve set up adequate technical processes to ensure that you’re getting returns. This is easier for smaller businesses but can become central points when scaled to larger enterprises.
In 2021, global management consulting firm McKinsey surveyed 1,843 participants from varying regions, company sizes, industries, and seniority levels. They found that AI adoption is continuing to rise, with AI high performers (companies that can attribute at least 20% of their earnings before interest and taxes to AI usage) outranking their peers in several best practices.
Some key AI best practices included:
Having well-defined processes around data governance and data security
Creating and maintaining protocols to ensure good data quality
Testing AI performance internally before going live
Setting up AI metrics and monitoring results
Testing and validating AI performance through third-party services
Creating a process to ensure that data is explainable
Training users and upskilling tech personnel on AI model capabilities
Rapidly integrate structured data to use for AI initiatives
Our key takeaway? You have to have proper protocols to ensure that your organization’s data is safe. Do not feed sensitive data into the AI model unless your IT infrastructure is secure. Additionally, AI is not perfect. Most AI high performers incorporate human touchpoints to monitor AI output and troubleshoot issues. Defining success metrics can also help you hit your goals when using AI for business.
Regarding AI adoption, it’s crucial to build internal trust to encourage your team to use AI tools. Even the most efficient tool won’t gain traction if no one wants to use it.
McKinsey researchers found that AI high performers emphasized the importance of explainable data and institutional safeguards to build internal trust. What data do AI models use? Are there legal or ethical ramifications to consider? How does the AI model draw its conclusions, and should we trust them?
Explainable data gives you insights into the AI’s “thought” process. This, in turn, empowers you to better explain the model’s outcomes and invest in tools and protocols that support them.
McKinsey’s survey is consistent with the University of Queensland and KPMG’s 2023 global study on trust in AI. Researchers found that those who had a greater comprehension of AI and its benefits were more likely to trust AI models. A positive perception of strong institutional safeguards (e.g., laws, regulations, organizational procedures) was the top driver of AI trust.
While understanding AI’s risks created uncertainty, it wasn’t necessarily enough to deter overall trust in AI. In fact, survey respondents in emerging economies such as Brazil, India, China, and South Africa have more positive attitudes toward AI despite reporting higher perceptions of risk. This may translate to higher AI adoption in emerging economies, which McKinsey’s study supports (57% of respondents in emerging economies report adoption).
Future Trends in AI
Whether you’re an avid fan of AI integration or are wary of the potential risks of unregulated AI usage, it’s clear that AI is here to stay. Businesses and organizations across the board are continuing to explore AI tools to streamline processes. And AI technology will likely lay the foundation for future technical tools that will further disrupt industries.
Before you adopt AI for business, create protocols around:
Protecting sensitive company and user data
Evaluating AI outputs for efficiency and value-add
Correcting AI outputs to suit your content needs
Training or upskilling your team on internal guidelines, best practices, and benefits to build trust and encourage adoption
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