In our increasingly competitive business world, finding an edge over the competition is essential for a company's survival. Generative artificial intelligence (AI) may be able to provide that edge for your business. From content generation to product design, generative AI holds the potential to optimize and revolutionize various aspects of business operations.
"I think AI is going to be the greatest force for economic empowerment and a lot of people getting rich we have ever seen," said Sam Altman, CEO of OpenAI.
However transformative generative AI may be, understanding its nuances and being able to integrate it into workflows effectively can be a challenge. Below, several business leaders provide insight into maximizing generative AI for business purposes.
What Is Generative AI?
A robust understanding of what generative AI is and how it functions is essential to harness its power for your business successfully.
"There's a lot of misconception out there about AI," explained Justin Soleimani, Co-Founder of Tumble. "It isn't just chatbots. When successfully implemented, it can automate rote tasks, find patterns, and even create original content."
Generative AI refers to a class of algorithms that are trained to generate new content that mimics real-world examples. Unlike traditional AI models that are designed for specific tasks, such as image classification or natural language processing, generative AI focuses on creativity and innovation. In other words, it has the ability to generate realistic images, text, music, and entire designs completely autonomously.
Industry Applications
Far from being limited to niche sectors, generative AI has immense potential across various industries, including marketing, e-commerce, healthcare, and entertainment.
"There's an application for artificial intelligence in almost every workplace," said Andrew Chen, Chief Product Officer of CommentSold, a company that specializes in Shopify live selling. "The limit is less based on what AI can do and more based on the business owner's imagination and commitment to learning these new tools."
Potential applications include personalizing recommendations for customers browsing an online storefront, designing new products and content, and highly specialized tasks, such as drug discovery in the pharmaceutical industry. Let's explore these in further depth below.
1. Content Generation
Consider using generative AI to automate content creation for marketing campaigns, social media posts, and website articles.
"Step one of leveraging AI for content creation is finding a data set to provide base content for that AI tool to learn from," shared Brandon Adcock, Co-Founder and CEO of Instaflex, a company known for their Instaflex Advanced joint supplement. "That might include previous marketing and social media content, historic customer data, or blog posts from your website."
Using AI to generate content aligned with your brand saves time and resources while providing a consistent flow of engaging content tailored to the target audience. After the initial hurdle of learning the technology and streamlining the generation process, content creation will be much easier and more efficient.
2. Product Design
In industries such as the fashion and automotive sectors, generative AI can assist in product design by generating multiple design variations based on specified criteria. Businesses can input parameters such as design constraints, customer preferences, and functional requirements into the AI model, which will then provide a variety of designs to be narrowed down and iterated by the production team.
"Getting the hang of AI-assisted product design can be a game-changer as far as speeding up the production cycle," said George Fraguio, Vice President of Bridge Lending at Vaster. "There's a learning curve, yes, but the payoff of cutting down on the time and labor required to generate ideas is absolutely worth it."
Generative AI can lead to breakthrough innovations and competitive advantages in the marketplace as well. Quicker production cycles allow more time for creative problem-solving and collaboration in your workforce, which can give you the edge you need to get ahead.
3. Personalized Recommendations
These days, personalized shopping recommendations have become almost expected among online consumers. These recommendations, based on customer browsing history, are largely powered by generative AI.
"AI-based shopping algorithms have become so commonplace that browsing an e-commerce site that doesn't use these tools can feel jarring to shoppers," warned Wendy Strgar, Founder and Chief Innovation Officer of Good Clean Love, a company that specializes in fertility lubricant. "Consumers have become used to seeing suggestions highly tailored to their individual preferences."
Personalized recommendations turn the sometimes soul-crushing experience of online shopping into an adventure, where every new purchase can yield unexpected and exciting new products. This enhanced shopping experience increases both conversion rates and overall sales.
Challenges and Considerations
Although generative AI holds promise for businesses across industries, integrating it into business processes comes with challenges and considerations. To start, there's the initial learning curve required to master any new technology.
"Implementing generative AI into an already existing business infrastructure can be hugely intimidating," advised Kiana Lake, Co-Founder of LUXE Pickleball. "There's definitely an initial time and labor investment unless you're already familiar with these technologies."
Potential obstacles to smooth implementation include ensuring customer privacy and security, eliminating biases, and maintaining quality control. Although daunting, approaching AI implementation strategically will go a long way toward managing these challenges.
1. Data Privacy and Security
Generative AI models require huge amounts of data to be trained effectively. However, this raises concerns regarding data privacy and security, especially when dealing with sensitive information such as customer data or proprietary research.
"Customer privacy and security are paramount for any business, but especially when implementing new processes that specifically require data to train on," shared Viktor Sobiecki, Chief Technological Officer of Digital Forensics Corp, a company that advises on how to protect yourself from disgruntled employees. "Secure data storage, anonymization, and aggregation are all essential steps in protecting the personal information that may be attached to that data."
Implement robust security measures to safeguard sensitive data, such as encryption and trusted cloud storage tools. Consider hiring a third-party vendor to ensure your AI model training adheres to security standards and compliance requirements.
2. Bias and Fairness
Like any AI system, generative models are susceptible to biases present in the training data. Businesses must be vigilant in identifying and mitigating biases to ensure fair and ethical outcomes.
"It isn't difficult to find examples of AI absorbing biases passed down from the data sets they train on," explained Bridget Reed, VP of Content at The Word Counter, a random word generator website. "As a business leader, it's your job to set structures in place that eliminate these biases and ensure all customers are treated fairly by the AI tools you choose to use."
One way to do this is by curating datasets to ensure they represent a diverse customer base and creating a diverse and inclusive implementation team. You may also consider using more advanced tools, such as data augmentation and adversarial debiasing.
3. Quality Control
Generating high-quality outputs consistently can be challenging, as generative AI models may produce undesirable or nonsensical results. Robust quality control measures, therefore, are essential to maintain the integrity of the generated content.
"AI isn't going to be able to do as good of a job as a human can," shared Greg Hannley, Founder and CEO of Soba Texas. "The technology just isn't there yet. So, it's important for any process that utilizes AI to have appropriate quality assurance and quality control measures in place to ensure the best product possible for the customer."
Establishing clear guidelines and standards for the tone and quality of the content produced by AI, as well as a multi-step review process, can help assure quality. Other automated tools, such as natural language processing algorithms, can flag potential errors.
What Are the Best Practices for Generative AI Implementation?
Before incorporating generative AI into your workplace, it's a good idea to develop a set of best practices to maximize your business's success. Simple steps, such as starting small and scaling up AI usage as you gain confidence with the technology, can ease the transition and prevent major problems before they occur.
"AI might be new tech, but there is already an abundance of resources out there to help train new folks on using these tools in a business setting," said Francesco Gatti, CEO of Opensend. "Seeking guidance from experts and using existing resources to learn the ropes is essential for the adoption of any emerging technology, including this one."
Aside from beginning with smaller applications and seeking external resources, continuously monitoring and evaluating your AI usage is another vital best practice you should aim to adopt. Gathering feedback from customers and from your own QA/QC department will ensure that you catch problems before they snowball.
An Unprecedented New World
Generative AI presents an incredible opportunity for businesses to innovate, streamline operations, and enhance customer experiences. However, a robust understanding of the applications and potential challenges of this technology is essential to fully harness its power.
As Jeff Maggioncalda, CEO of Coursera, asked, "Is it perfect? No. Is it as good as my executive team? No. Is it really, really valuable, so valuable that I talk to ChatGPT every single day? Yes."
As technology continues to evolve, embracing generative AI will become increasingly essential to staying ahead of the competition. Rather than let your business fall behind, if you learn the ins and outs of generative AI now, you just may find yourself shaping the future of business.
