IS YOUR ORGANIZATION AI READY

By David Ramirez

Events organizations the world over have already experienced the transformative power of artificial intelligence to enhance and optimize their work. Over the past year, countless software solutions used by event professionals have added AI-assisted features, allowing them to experiment with AI without adding new brand technology to their Stacks1.

Now that AI has proliferated across tools and industries, organizations need to establish policies and procedures to manage the usage and implementation of these technologies across all departments and levels of an organization. Having a strategic framework at the organizational level is vital as more professionals utilize these tools to ideate, create, and execute events.

While this article will primarily address organizational concerns about artificial intelligence, the same framework can be applied to any modernization efforts to pull groups forward and remove tech debt2

Organizational AI plans should cover each of these three areas.

1. Start with Data

2. Establish Policies for Use

3. Plan to Scale and Educate

Event Culture Guides the Plan

American architect Louis Sullivan said, “Form Follows Function”. The culture and structure of an events organization are the ideal starting points for establishing policy. Smaller, newer organizations are generally more agile than larger, more established events. It may be easier to launch a technology initiative in a single department or team before growing it to the entire workforce. Some event organizations embrace change, while others may take a more conservative approach to change management.

Regardless of the organization’s size, there must be room for experimentation. Incorporating AI at an organizational level will likely have false starts, unforeseen obstacles, and growing pains. These friction points should not dissuade event professionals from integrating new technology into their workflows.

1. Start With Data

Artificial Intelligence, in all its varieties, requires large amounts of data to be productive. Some models, like ChatGPT or Google Gemini (previously Bard), are trained on established data sets, known as Large Language Models. This can be useful for generative output, such as writing marketing copy or updating volunteer handbooks. However, constant data is needed to feed the machine to create valuable outputs that will give events a competitive edge.

One of the greatest opportunities of AI implementation is in tracking revenue and productivity. Organizations typically spend weeks crunching ticketing data and attendee feedback to find trends. Now, tools incorporate analysis models to find macro- and micro-trends in near-real time.

Feeding The Data Machine

This is an exciting proposition on paper, but the reality is that many events are ill-prepared to centralize their data in a useful way for processing. Data silos exist even in smaller organizations. Marketing may hold the information from feedback surveys and ticketing information. Operations may have volunteer and staff reporting, along with vendor feedback. Sponsorship has results specific to their own activations. And this gets more complex as events get bigger.

AI gets smarter as it is trained with information. How does your organization organize and maintain records across departments, events, and time? Do you have a large enough body of information to get results from an AI tool?

Looking Towards the Future

Many robust data tools remain out of budgetary or technical reach for many organizations. However, as these technologies become more mainstream and less expensive, event professionals will likely be investing in data lakes or warehousing tools to centralize and organize information in the future.

2. Establish Policies for Use

The biggest transition into organizational AI is establishing policies that govern use across teams. For many events, it is the wild west. Staff can test, implement, and use tools without seeking approval or permission. Most existing technology use policies do not accurately cover the many AI tools that have popped up overnight.

The ideal AI policy is not intended to be restrictive but rather provide guardrails that allow staff to still experiment and grow while maintaining the safety and integrity of the organization.

Empowered Use and Decision Making… with Scrutiny

As the glamor of Generative AI3 wears thin, Predictive AI4 has the potential to advance events by analyzing and forecasting the results of everything from ticket revenue to new program elements to the draw of performers. But we’re still far from having a crystal ball that allows us to see into our event’s future.

What Can Be Released into the Wild?

Until the technology matures, everything produced by AI should be scrutinized in the same way one would review the work of an intern. Delight in the quality of work, but always check the spelling and math. Even well-trained enterprise-grade technology will occasionally hiccup and struggle with rudimentary tasks. A review by management or leadership should be a mandated step, particularly for elements or content that cannot be easily recalled like print media or public relations announcements.

Understanding that AI is not infallible, ensure all staff and stakeholders know what AI uses are permitted internally and externally.

Seek Consistency

Event organizations have unique voices that reflect the vibrancy of their communities. Leaning on AI to write content or create media can put those voices at risk. A well-crafted digital policy will allow people to use these time-saving tools while still maintaining the charm that many attendees and stakeholders expect.

The most straightforward consistency measure is establishing a set of parameters to use as an initial input when prompting an AI tool. Is your event’s style funny, sarcastic, country, metropolitan, or elite? Do you have a specific tone or tenor to your communication? Are there in-jokes or references that people expect? A prompt, used by all staff to “set the scene” for any AI tool, will ensure some amount of consistency.

Larger organizations may find that prompt engineering is not enough. Tools like Grammarly and Claude allow organizations to take a more active role in establishing brand guidelines and tone at an administrative level, then pushing it into the software used by all teams.

Consistency is king in communication. Consider how you’re maintaining a voice across the myriad tools and technologies that your team uses.

Data Privacy and Cybersecurity

Be mindful that many AI tools are trained on the information put into them. Understanding the privacy implications of any technology should be part of the due diligence when deploying AI or any tool organization-wide.

The ideal privacy policy will vary by organization. Basic anonymization or scrubbing of Personally Identifiable Information (PII) is a good place to start. Check with your lawyer or other qualified counsel to see if your organization has specific privacy requirements based on size or location. Also, consider how attendees and other stakeholders may react if they discover their information is being uploaded into a tool without their knowledge.

This may be a good time to update any existing data privacy and cybersecurity policies.

3. Plan to Scale and Educate

Robert Burns wrote, “The best-laid plans of mice and men often go awry.” Without a plan to scale and educate, any attempt to roll out a technology organization-wide will lead to nothing but grief and pain. The scaling plan should consider short-term and long-term goals and equip the human capital with skills to use and maintain the technology effectively.

Short-Term Goals

Short-term plans should seek immediate efficiencies and allow room for feasibility testing. Many event organizations have already found these short-term results with AI appearing in existing tools like email marketing software and CRMs.

Budget and time should be allocated for experiments with technology and processes that can bring improved results to an event. Staff should be reassured that these experiments are not to reduce headcount but to augment tasks to allow staff to spend more time being creative and focusing on producing events.

Some of these experiments and tests will fail. Staff should feel empowered to “Fail Forward” and share their learnings with others who may be exploring similar avenues. Maybe share best practices during an IFEA Affinity Group?

Long-Term Goals

During short-term experiences, teams will likely encounter software solutions that are too expensive, too difficult to use, or too data-intensive to be implemented viably. Understanding the Technology Growth Cycle5, we’re still in the Innovation and Growth stages. Don’t disqualify or exclude a specific technology because it is too expensive or difficult today. Technology will slowly stabilize over time, prices will decrease, and technical requirements will become more accessible. Using feedback from the short-term experiments will guide future plans.

Long-term technology plans should not take place in a vacuum. Add technology as a strategic pillar in your organizational plan. Make sure your technology goals align with other organizational goals. Technology should not be a philosophical friction point in the future of an event organization.

Education is Fundamental

Education is fundamental when deploying organization-wide AI. It supports employees of all levels with the understanding and skills necessary to harness the technology’s potential. Leaders must understand and grasp its strategic value. Management staff must continuously be trained to administer AI solutions. Even frontline workers and volunteers must be able to use or engage with the tools. A strong education component establishes a culture of innovation and helps people and organizations navigate the complexities of this swiftly evolving technology.

Is Your Organization AI Ready?

Adding any new technology, let alone artificial intelligence, can be a daunting task. But, as with any major organizational change, success should be measured in months and quarters, not days and weeks. Artificial intelligence is already making seismic changes in our industry. There are so many opportunities for those who are ready to embrace it. Implement it intelligently. Move with purpose. And don’t forget, you still have that event next week.

1 Stacks or Tech Stacks: The combination of technology and software an organization uses to accomplish its goals. This can include website tools, CRMs, email tools, task management software, people management tools, marketing technology, general hardware preferences (i.e., Apple vs Windows), mobile technologies, and more.

2 Tech Debt: Borrowed from Software Development. Tech Debt refers to the practice of relying on temporary, easy-to-implement solutions to achieve short-term results at the expense of efficiency in the long run. Resolving debt requires groups to invest more significantly in modernizing technology, infrastructure, and talent. (Edvantis)

3 Generative AI: Generative AI or generative artificial intelligence refers to using AI to create new content, like text, images, music, audio, and videos. Generative AI is powered by foundation models (large AI models) that can multi-task and perform out-of-the-box tasks, including summarization, Q&A, classification, and more. (Google)

4 Predictive AI: A computer program’s ability to use statistical analysis to identify patterns, anticipate behaviors, and forecast future events. Predictive AI makes statistical analysis faster and (theoretically) more accurate via machine learning and access to vast amounts of data. (Cloudflare)

5 Technology Growth Cycle: The natural lifecycle of a technology or product. Technology starts with the Innovation Stage, where many rapid breakthroughs and developments happen. Then, it moves into the Growth Stage with widespread adoption and proliferation. Then, Technology moves into the Maturity Stage, where it becomes standardized and established as part of everyday life. Finally, it goes into Decline or Substitution, where it is phased out or replaced by a new technology.

The framework of this article was inspired by “Building the AI-Powered Organization,” which appeared in the July-August 2019 issue (pp. 62-73) of Harvard Business Review. A version of the article can be found at hbr.org/2019/07/building-the-ai-powered-organization

S. David Ramirez is an award-winning marketing and communications professional from San Antonio, Texas. He is the Senior Marketing Manager for Partnerships and Events at TINT, the community-powered marketing platform. He is the founder and principal consultant at SDMRamirez, an event strategies agency serving festivals and events nationwide. David is a subject expert in social, digital, and event marketing, presenting at countless events and webinars, including Adweek Social Media Week North America, Social Media Week Los Angeles, Digital Summit Dallas, Internet Summit Raleigh, and a recent plenary on Artificial Intelligence in Event Management at the International Festivals and Events Association annual conference. David is a frequent contributor to the Texas Event Management Institute and the U.T.S.A. Institute for Economic Development. He serves on the International Festivals and Events Association Foundation and the Texas Festivals and Events Association boards. Mostly, he’s a nerd. Talk to him about anime, craft beers, and science fiction.