From recent ChatGPT updates to the newly launched Microsoft Copilot, the rise of more expensive AI technologies is spotlighting an emerging digital divide among businesses. We unpack the nuances of the AI digital divide and provide scrappy strategies for small- and medium-sized businesses to compete with large corporations with deep pockets.
On November 1, 2023, Microsoft launched Copilot, an “AI companions” suite designed to enhance various Microsoft platforms, from 365 to Sales. Seamlessly incorporated into Microsoft applications, Copilot allows its users to access AI-powered insights without leaving the app to go to an external browser, ultimately elevating their Microsoft experience and boosting their productivity. Plus, Copilot is trained on your organization’s data, meaning its results are tailored to your business and its priorities.
Less than one week after the Copilot launch and during its first-ever development conference, OpenAI announced several new updates to its popular generative AI tool ChatGPT, including a newer model, GPT-4-Turbo, and the ability to collaborate with OpenAI developers to customize GPT-4 models for your business — both of which we will unpack later.
Microsoft and OpenAI’s latest advancements signal a significant leap forward in the potential of AI technologies to transform everyday business life. Unfortunately, with their large price tags and significant seat minimums, both are more accessible to larger Fortune 500 organizations rather than small- to medium-sized businesses (SMBs).
To start, Microsoft 365 Copilot requires at least 300 users and costs $30 per user per month. (To do some quick math, if your organization purchases Copilot, it will spend $9,000 per month and $108,000 annually — at minimum.) Additionally, to purchase Copilot, your organization needs to have one of two Microsoft 365 licensing plans: the M365 E3, priced at $36 per user per month, or the M365 E5, priced at $57 per user per month.
Similarly, OpenAI’s ChatGPT Enterprise licensing requires at least 150 users and costs $60 per user per month, also totaling $108,000 per year. And, if you would like to create a customized, internal-only ChatGPT with OpenAI developers, you must submit a form for consideration and acknowledge that pricing starts at $2 to $3 million. Yikes.
The key message here is that quality AI is not cheap. It’s easy to see how the costs of these advanced tools are prohibitive for all but the largest businesses, thereby creating an AI digital divide.
In this article, we’ll introduce the latest AI updates, present the risks of a digital divide, and share scrappy strategies that businesses can use to compete with large organizations while saving money and enjoying the advantages of generative AI.
Introducing the New Era of OpenAI
ChatGPT-4-Turbo
The name says it all: ChatGPT-4-Turbo presents a more advanced, high-powered version of ChatGPT. ChatGPT-3.5, the free model released in November 2022, and ChatGPT-4, an updated paid model released in March 2023, have the same knowledge cutoff of September 2021, meaning they do not have access to information beyond that date. By contrast, ChatGPT-4-Turbo has a knowledge cutoff of April 2023. (For example, while GPT-4-Turbo may recognize the term “Eras Tour,” no ChatGPT model knows that Taylor Swift and Travis Kelce are dating.)
Additionally, GPT-4-Turbo enables in-depth and complex interactions with ChatGPT, creating a richer and more versatile user experience. It boasts an impressive token limit of approximately 15.6 times that of GPT-4 and 31.25 times that of GPT-3.5.
In this context, tokens are common units of characters, sometimes corresponding with syllables and words, but not always. For example, both “the” and “Microsoft” are one token, while my name “Joseph Ours” is three. A token limit encompasses both our input and ChatGPT’s response. With GPT-4-Turbo’s 128,000 token limit, users can write far more extensive prompts and receive equally comprehensive responses — totaling roughly 100,000 words, the equivalent of 300 pages of material.
Custom Models
OpenAI has expressly stated that it will only invite select companies to collaborate with its developers in creating custom internal GPTs. With “billions of tokens at minimum” and “exclusive access to their custom models,” OpenAI promises a high-quality, tailored tool that endows chosen organizations with unprecedented capabilities. And, with a couple of million-dollar price tags, it’s safe to assume that this luxury service will only increase the technological advantage of large powerhouses.
The Risks of the AI Digital Divide
Executives may ask, “If I can’t afford these resources, why should they be important to me?” Here are three factors to consider:
Competitive Disadvantage
SMBs will struggle to compete with the efficiency, speed and innovation of larger companies that use advanced AI resources.
Although Microsoft Copilot and newer OpenAI features come with a hefty price tag, they are well within reach of large organizations with substantial resources. By contrast, it is highly unlikely that the average SMB could afford these tools. Even if price isn’t the excluding factor, company size may be: Copilot is unavailable to businesses with fewer than 300 employees, and ChatGPT Enterprise is inaccessible to those with less than 150.
Armed with the latest AI resources, larger companies will gain a significant edge in productivity and efficiency, producing high-quality, strategic content, goods, and services at reduced costs. These new, flashy (and cheaper) services will strengthen large organizations’ already extensive brand recognition.
Customers inherently place their trust in well-known brands, particularly those that showcase their innovations, making it challenging for smaller businesses that lack the recognition and resources to establish themselves as viable competitors. The combination of cost, size, speed, and innovation could hinder SMBs’ ability to keep up with — much less outpace — larger companies.
Market Monopolization
As larger companies increasingly adopt advanced AI resources, they could monopolize market sectors, making it harder for smaller businesses to survive.
As large businesses across multiple sectors invest in Microsoft Copilot and Enterprise ChatGPT or develop their own generative AI models, they gain a significant edge in the market. With a pool of skilled AI professionals and ample data to train their models, these large companies can easily create robust AI tools, increasing their dominance within their respective industries.
With their ability to shape innovative trends and set market standards, large organizations create a challenging environment for SMBs to compete.
Innovation Stagnation
Without access to advanced generative AI tools, smaller companies will find it difficult to innovate, leading to a less diverse business ecosystem.
Swept up in the buzz of the latest technologies, SMBs may observe the innovations of their large competitors and feel dissatisfied with their current approach to business. However, without the funds to purchase and maintain these expensive tools, smaller organizations have limited opportunities to introduce new products, services and technologies into their digital environment.
In this clear gap of access, larger companies enjoy a distinct advantage, fostering an environment where innovation is the norm, while smaller companies feel stuck by their inability to harness specific generative AI tools.
Unless they adopt a strategic approach to innovation rather than relying solely on technology, large companies might weed out SMBs, leading to a less diverse business ecosystem. Put simply, to compete, SMBs need to get scrappy.
While the risks of an AI digital divide are real, they’re amplified by a specific mindset, one that prioritizes specific vendors and products over solid strategy. Taking a few steps back to reflect on precisely what you aim to achieve with AI can illuminate a more (cost) effective path forward.
Bridging the Gap: Scrappy AI Strategies
By assessing the following sound strategies, organizations can uncover several ways to tap into the benefits of generative AI without compromising their budget, mission and goals.
Invest in AI Strategically
Strategically investing in AI does not mean matching the spending of large corporations but rather pinpointing cost-effective AI solutions that offer the most significant return on investment (ROI) for your specific needs. While large institutions can usually afford the latest and the greatest, that doesn’t mean their investments are strategic or successful.
In fact, large institutions tend to be inefficient with innovation investments, spending money on products and technologies that sound good but do not provide substantial value to their organization.
Instead of waiting for technologies to become affordable, SMEs should explore innovative ways to integrate AI into their existing operations, even on a smaller scale. For example, retail businesses using Shopify should consider incorporating Shopify Magic, AI-powered tools that assist in writing marketing materials from product descriptions to emails, into their operations. AI not only helps business owners create content, but also optimizes content strategy. A Forbes article on AI transformation in small businesses notes that “AI is smart enough to understand what individual customers are looking for, and it can draw on their behavior and preferences to recommend the best content, channel, and time to send a message. If you’re a small business owner, that type of personalization and recommendation engine is invaluable because it will enable you to send the right messages to the right people at the right time – and in the right channels.”
Introducing AI one feature at a time, however small, allows you to build its presence in your business modularly, focusing on small, incremental uses to reduce risk and tailor a strategy that aligns with your organization’s unique goals. This approach allows SMBs to control their expenses, customize AI to their needs and business model, and grow its presence in their business at their discretion.
By selecting generative AI tools that align with their budget, organizational goals, and specific operational requirements, SMBs can tap into the kind of innovation they want without an expensive, multi-year initiative to replace all their technology with new parts. Instead, they can swap out technologies as they see fit to create the ideal digital environment for them.
Additionally, a modular environment is more conducive to employee training in AI literacy. By training employees in smaller, more focused tasks, businesses can ensure their employees acquire the skills they need without feeling overwhelmed. This deliberate, supportive approach to learning fosters a culture of continuous improvement, allowing individuals to apply AI concepts incrementally to their specific roles, creating a more AI-literate workforce that uses strategic resources and understands their applications.
Avoid Vendor Lock-In
Don’t rely on one vendor, whether that be OpenAI or Microsoft, to fulfill all of your needs. Keep your options as open as possible, using several AI providers to protect your organization’s assets. As new generative AI models continue to emerge, the market will become increasingly competitive, even volatile, as demonstrated by the recent tumultuous events at OpenAI. Protect your organization’s needs first. Worry about specific vendors later. The greatest risk to your organization is not having a scrappy plan.
For example, one of our clients wanted to implement ChatGPT on a large scale to optimize their operations. Instead of exclusively committing to OpenAI, we encouraged our client to identify their core business objectives and to reflect on what aspects of their operations would benefit the most from AI.
After we provided over forty potential AI applications, our client decided to train chatbots and create data forecasting models that would allow them to predict what services their customers wanted the most. By taking a more strategic approach to AI implementation, our client gained a deeper understanding of their customers and could better meet their needs.
Use Scaled-Down AI Resources
While SMBs may not be able to afford internal GPTs, they have access to other customizable resources offered by OpenAI. To create a chatbot tailored to your organization or even your specific work style, you can build your own ChatGPT (called “GPT” for short) — no coding (or $2 to $3 million developers) required.
To create your own GPT, you need to purchase a ChatGPT Plus subscription, priced at $20 per month or just $240 per year. Once you create your account, simply type your instructions into the GPT Builder, such as, “Create a chatbot that generates lesson plans.”
GPTs can be strategic or unserious. For example, the New York Times suggests that a bed and breakfast make a GPT to answer their guests’ questions. Similarly, an academic writing tutor could make a GPT to evaluate students’ thesis statements. By contrast, a Zapier article shows readers how to build a GPT that spews out witty otter trivia.
Additionally, individuals can share their custom chatbots with others through the GPT Store, OpenAI’s version of an app store. The creators of these customized GPTs can earn commissions based on how many people use their chatbot.
If you’re concerned about the security of your organization’s data, you can keep your GPT private and opt out of model training, meaning that OpenAI will not use your data to improve its models. These lower-priced GPTs present a much smaller investment that has an equally great potential for innovation.
Consider Open-Source AI
In addition to creating custom GPTs, consider open-source AI, which allows anyone, regardless of their professional affiliation, to access and modify source code for their own projects or business initiatives. While open-source may not offer the same capabilities as more expensive enterprise options, The MIT Sloan Management Review notes that open-source AI can significantly boost productivity and innovation.
Don’t let comparisons to highly complex tools prevent you from taking advantage of a free resource with multiple benefits. However, don’t let open-source’s lack of price tag distract you from taking proper precautions: since anyone can modify open-source code, you must always consider reliability and your data privacy.
Double Down on Human Relations
As good as AI is, it is not a substitute for solid customer relations. Take, for example, retail sectors, in which customers value face-to-face connection and personalized services. In these environments, human understanding and empathy enhance customer satisfaction and loyalty, which far outweighs the efficiency of chatbots or any form of AI communication. In markets where the human touch is essential, balance the desire to use AI innovations with the irreplaceable benefits of personal communication.
By considering these five factors, you can make your next AI move from a proactive, not reactive, stance.
Navigate the AI Digital Divide
The recent advancements in generative AI foreshadow a business digital divide that will challenge all but the largest of companies. While large corporations may have the financial advantage, that doesn’t mean smaller businesses are without options. Adopting a scrappy approach driven by strategy, collaboration, and innovation will allow you to effectively navigate this new landscape without compromising your budgets or their goals.
The key lies in recognizing the potential of AI and harnessing it in a way that aligns with your unique business model and financial capabilities. By doing so, your organization has as much potential to thrive in this new era of AI-driven business.
AI is rapidly evolving beyond the familiar chatbots. While many leaders use tools like ChatGPT to increase productivity, AI agents will transform how businesses operate entirely. If you want to stay ahead in the AI arms race and drive significant returns, this executive session is for you
