Feel a little lost with all the chatter around artificial intelligence? This guide aims to help. AI’s perks are evolving, but you can still benefit.
You probably have heard a little bit about artificial intelligence in the past year or so. It’s, simply put, been hard to ignore, and many mainstream applications, big and small, have tried to put their twist on the recent trends in large language models and generative art.
The association space, with the structural backing of volunteer boards, has traditionally moved more carefully than the move-fast-and-break-things mindset of the startup world. As a result, many tech companies have already started to implement the benefits of AI Tools … but you may not quite be there yet.
Given the iterative and disruptive nature of the technology, that isn’t necessarily a bad thing, or even uncommon. A survey from the professional services firm KPMG found that nearly two-thirds (65%) of U.S. executives saw AI as having a major impact over the next 3-5 years. But another 60% say that they’re a year or more from implementing anything.
To put it another way, if you’re still analyzing the potential for artificial intelligence applications at the moment, don’t feel discouraged. But don’t just sit the moment out, either.
The excitement for the technology is high, but implementing it within your organization is going to require some thinking. You may even find that your own employees are using it to make smaller tasks easier without your realizing it.
So what is Artificial Intelligence, Anyway?
Artificial intelligence, when you break it down, refers to the way information is parsed by computers.
Starting from a basis of automation—the idea of repeating a task without human intervention—AI has become a key element of modern computing. With its earliest forms dating to the 1940s and 1950s, this technology has, like processing power, been held up as a primary sign of innovation in the technology space.
AI is moving quickly, with some of its fastest evolutions happening within the past six months.
Given all that, there’s a lot to catch up on. A few common terms you may run into around AI:
Machine learning. This refers to the development of technology, such as algorithms, that allow machines to “learn,” or simulate thought, through the analysis and gathering of data. A related term is the neural network, which refers to a cluster of data points that interact with one another—a technique essential to modern machine learning. Machine learning is at the center of many of the recent advances in AI.
Natural language processing. A method in which computers can capably parse and understand text and speech, using that information to parse queries or navigate conversations.
Conversational AI. This approach to artificial intelligence, most prominently seen in chatbot technologies such as OpenAI’s ChatGPT, has perhaps seen the most dramatic growth in capabilities over the past year, as large-language models (LLMs) have improved to a level where it feels like you’re talking to a real person.
Generative AI. Perhaps the most experimental form of modern artificial intelligence, this refers to attempts by computers to create content generated from information models, particularly large-language models (LLMs), to create artistic works whole cloth, often from prompts. This type of AI has been controversial due to its perceived economic impact.
Companies that rely on AI often offload the computing power it requires to the cloud, a technology that has played a major role in its modern growth. The cloud-based nature of AI shows itself another way, too: One thing you’ll likely find in the modern day is that many individual employees are likely already leveraging AI through software-as-a-service tools like Otter.ai, which can convert recordings to text, and Anyword, which can help write social media posts.
There’s no guarantee that the rapid evolution of AI will continue forever—in fact, its biggest innovations have happened in fits and starts. What matters more than anything is the value you can grasp from this technology.
The AI Winter: When AI Loses its Hype
AI’s long history, dating back to the 1950s and 1960s, has been shaped as much by its down periods as its periods of growth.
Those down periods even have a name—“AI winters,” which took place from 1974 to 1980 and from 1987 to 1994. These periods came after strong periods of excitement about artificial intelligence that ultimately did not live up to broader expectations, leading to drops in investment.
More recently, growing investment has helped push forth a resurgence in AI innovation, particularly in the form of “deep learning,” which has created new interest in the technology while tamping down more unrealistic expectations.
It’s entirely possible that AI’s potential won’t live up to the hype. After all, AI fits in Gartner’s Hype Cycle, just like every other type of technology. But it’s also entirely possible that it could lead to some real benefits.
Should Associations Be Concerned?
Recently, a Gartner analysis predicted that by 2025, roughly 30% of marketing messages could be created using generative AI tools—a huge leap from the mere 2% used in 2022.
That data point highlights the uncertainty that artificial intelligence has created in some industries—is it going to replace the work of regular people, or disrupt your existing model?
There are genuine concerns out there that new kinds of companies or organizations will emerge that could compete with your existing technology by building faster than your organization ever can. Earlier this year, a marketer went viral for building a site that generated massive amounts of traffic from content generated entirely with artificial intelligence tools.
But there’s another lingering tension as well. As anyone in the C-suite is aware, there’s always lingering pressure to find ways to cut costs, and AI could be a way to save money, or perhaps boost productivity. But that could come with ethical issues of its own. As a professor at the University of California, Los Angeles put it in a recent Washington Post story: “[AI] is coming for the jobs that were supposed to be automation-proof.”
This approach may go against your mission as an association. For example, a journalism or artistic association would probably not want to lean heavily on generative content.
And it’s worth keeping in mind that human creators have a reputation for quality—and AI has a reputation for making things up and being repetitive. (They are seen as a potential source of disinformation.) If you’re bringing in AI to cut corners, it’s going to eventually show.
Where Does AI Stand Now?
At this time, we are not in an AI winter—rather, we’re deep in an AI summer, one that many businesses are leverages to find use cases that make sense for their needs, associations included.
Associations are often leveraging sites, platforms, and design paradigms that may not be the most up to date, and that creates challenges that might lead to lots of busywork. (Tagging, for example, is an essential organization tool for complex content platforms, but human editors often forget about it.) AI, if implemented carefully, could be a way to simplify the busywork, allowing your team to focus on a higher level.
Among the areas where it could make sense for associations:
Member segmentation. Trying to break down shifting member segments manually can take a lot of time, even for seasoned membership pros. Utilizing machine learning and natural language processing in your data analysis, however, can make it easier to target members with benefits that best fit their needs.
Stronger member segmentation could allow organizations to better serve their members' unique needs and deliver greater value, fostering stronger and more loyal member relationships.
Predictive analytics. Think of this like you’re Wayne Gretzky—it’s the trick you use to see where the puck is going. This tactic takes advantage of the past cues—grabbed from your AMS or website analytics tools—to identify member needs and trending interests that your association can then build towards.
Improved analytics could allow for real-time adjustments and increased accuracy in forecasting future outcomes.
Automation. Both in the server room and throughout the day, there are always small tasks that need to be done to keep your association on task.
By building technology that can take these elements off your team’s plate, that frees them up to taking on tasks that they are more uniquely skilled to solve.
Content recommendation. Associations produce a lot of content, much of it hard to find or discover through traditional means on an association’s website. Having access to an individual user’s personal analytics can be a powerful tool that can ensure you’re reaching them with content that best meets their needs and interests.
AI, when implemented correctly, could supercharge your search, while giving your readers highly personalized recommendations.
Marketing. Marketing doesn’t just rely on the finished product anymore. Often it comes with a lot of additional needs, such as building copy for social posts, tagging content to maximize its searchability and accessibility, and generating daily emails.
Newer technologies, such as OpenAI’s GPT-4, make it possible to develop content from whole cloth.
Video. Video has increasingly become an important part of the media diet and education process for association pros and especially their members, but video is time-consuming to produce in digestible ways, requiring a lot of organization and metadata to make the most of it.
AI-based tools could help minimize some of the more complex parts of this, by helping to summarize the videos, creating searchable transcripts, breaking up videos into thematic chapters, and even parsing out key clips from education events and annual meeting sessions.
Playing Co-Pilot: Why Humans Still Matter With AI
One common thread in most of the above examples is that, while AI can offer a helping hand, it is not doing all the work. The human is ultimately still in charge of the final result, and that’s not an accident.
One thing that artificial intelligence cannot understand to the level of a human creator are contextual and social nuances. If you’re working on a creative project, you will naturally have a better understanding of what your board or executive director wants than an AI driven by your commands ever will.
The human touch also matters from an ethical standpoint. You represent the compass that will ensure that the decisions that AI makes are beneficial, rather than destructive. And that helps avoid unintended consequences.
Artificial intelligence can simplify and tackle complex problems. You can bring empathy and context to the daily scenarios where AI makes sense. Together, you can help solve challenging problems more effectively.
Parsing AI’s Potential for Associations
When a new technology like AI emerges, it often feels like associations are put into a position where they find themselves worried about how things are going to shake out, rather than taking advantage of the technology’s full potential.
One thing that could help, per Kevin Leonard, Breakthrough Technologies’ Director of Business Development, is to think of AI not as a replacement for existing workflows—but an enhancement.
“AI is not meant to replace human intelligence, but rather enhance it—and when integrated into a human-centric workflow, it becomes a catalyst for productivity and empowerment,” Leonard says.
Disruption is happening all the time in the technology world, and in that light, AI is likely your response to some other form of disruption you’re facing with your member base or technology needs.
A Forrester study commissioned by IBM found that more than 60% of advertising technology leaders saw AI as a potential way to meet challenges being created by broader market shifts, such as new regulations and the retiring of technologies like third-party cookies.
Your association may not be ready to make AI this year’s model. Implementing technology in a useful way takes time—after all, if you want to integrate it into your website or an app, you have to plan for that, so it meets your members’ needs and doesn’t feel tacked on.
And there’s always next year.
If you'd like to learn more about AI or would like to inquire about an AI based project for your association, please contact kevin.leonard@breaktech.com
PHOTO CREDITS: DAVID BECKER/UNSPLASH; CHARLES DELUVIO/UNSPLASH; JOHN SCHNOBRICH/UNSPLASH; ICONS VIA THE NOUN PROJECT