Speakers at 2024 FMG Symposium discuss the significance of the technology for retailers and what it could mean for their business
LAS VEGAS — As with any technology, businesses first have to learn about AI, then how to apply it to their business.
That was a key theme in a presentation at the FMG’s 33rd Symposium held here last week — “AI and What It Means for Furniture Retailers.”
Presented by White Shark Media CEO Daniel Alvarado and DispatchTrack CEO Satish Natarajan, the discussion offered some historical perspective about AI and to what degree business and marketing professionals see it affecting their business now and in the future.
Another key message was that while the technology is still evolving and far from perfect, it is moving more quickly than anyone realized possible even in the past few years.
“AI has been used in the past 12-15 years, but the difference now is that we can do it a billion times faster than we were able to do it 15 years ago,” Natarajan said.
And at the rate of adoption in today’s marketplace, many are jumping on the AI bandwagon to see how they can apply it to their operations.
“I too have to look at ways to implement it in my business so I can stay competitive,” Alvarado said of the way professionals are viewing the technology. “In future years it will simply be part of day to day.”
For many, the future is here now. Citing data from Stanford University and McKinsey, Alvarado’s presentation noted the following stats:
+ 35% of businesses globally are using AI
+ More than 42% of businesses are exploring the technology
+ $50 billion has been raised by Generative AI and AI startups
+ AI can unlock an estimated $2.6 trillion to $4 trillion in productivity
+ 31% of businesses list “competitive pressure” as a top reason for adopting AI
+ 34% say lack of AI skills and expertise is an adoption barrier
Meanwhile, some 85% of marketers agree that AI enhances content quality and prospecting efforts, while 76% of chief marketing officers believe that failure to adopt AI will “significantly hurt their ability to stay competitive.” And according to Hubspot, another 85% of execs say that generational AI will directly interact with customers in the next two years, while 30% of reps say that AI will reduce average handle time for customer service types of interactions.
Alvarado went on to explain various areas of AI, ranging from machine learning — which uses data to imitate how people learn and respond — to ChatGPT — which uses natural language processing to respond to verbal prompts and create detailed responses.
But as with any other technology, AI continues to evolve and is nowhere near perfect in its current form. For example, Alvarado noted, it can be utilizing data that is “biased, inaccurate or stale” and also tends to lack creativity. In addition to ethical and privacy concerns relating to the technology, it can be expensive to adopt as part of your business model.
But there are ways to make it work to one’s advantage:
+ Have a customer relationship management system in place to keep track of customer data and purchase history, for example.
+ Centralize data systems by breaking barriers between various systems such as a CRM or point of sale to “create a unified data store.”
+ Embrace AI-powered systems such as Google Ads, Bing, Salesforce, Hubspot and others that offer AI features without requiring a data team.
“You are going to have to go through a little bit of a process of trial and error to incorporate this into your day-to-day business,” Alvarado said.
Natarajan added that AI can be used in a number of ways, including personalizing product and content to match individual tastes. Such personalization can range from age, gender, income, language and homeownership to purchase history, social media activity and other interests.
He also noted that it can be helpful in areas such as predictive analysis in a way that optimizes product stock levels, achieves inventory efficiency as well as demand forecasting and predicting supplier performance and lead times, for example. In areas such as logistics, it can be used for delivery scheduling, route forecasting and optimization and predicting service quality and service times.
AI can help achieve route optimization, for example, by tapping into historical data and by using machine learning to build predictive models. And smart scheduling for deliveries, for example, can be achieved by using historical data, demand forecasting and fulfillment channel options.
And in a final note about how DispatchTrack views AI in the marketplace, Natarajan ended with a slide that noted, “Predictive analytics and generative AI are transforming all industries. We envision using AI to augment the decision making of your employees so they can be more efficient and effective.”
“This is happening at a faster pace,” Natarajan noted of the development, implementation and results of AI. “We can do more things at a faster pace.”