As technological innovations such Artificial Intelligence are reshaping our everyday lives, it can also be harnessed to improve the theme park industry by advancing theme park designs, the theme park design process, theme park operations, and take immersive experiences to a whole new level.
Currently, AI in more sophomoric forms are currently working to improve several of these aspects of the industry. While no one has a crystal ball to predict how AI and machine learning will impact the theme park industry over the next three to five years, we can use current and recent previous data to predict the evolution of theme park design and operations.
With respect to theme park designs, early forms of AI are being implemented on larger projects’ design processes such as incorporating augmented reality, virtual reality, and BIM enabled and metric based design implementation and integration. However, for those working to bring new theme park designs to fruition, there is an open field for improvements.
Artificial Intelligence Will Improve Theme Park Designs and Enhance the Design Process
The time between a theme park operator identifying the need for a new theme park project to opening day of said project – depending the size of the project – can take 3 to 10+ years. Imagine trying to design to project standards and the Guest’s desires for a project that may not come to fruition nearly a decade into the future – that in a nutshell is theme park design.
Guest’s tastes, desires, and expectations of a new theme park projects can change rapidly in that span of time. Incorporating AI into the early market research of understanding what theme park Guests expectations for new projects coupled with AI enabled design processes could assist project teams in getting new projects to market quicker and more in line with Guests desires.
Blue Sky Ideation
The Blue Sky design phase, unique to the theme park design process, is the first formal phase of design. In Blue Sky, nearly anything is possible as this is the phase where the story is commenced, ideas are formulated, generated, thrown out, etc. AI and machine learning could assist by producing multiple, more refined design ideations faster for review and to compare to the theme park operators program requirements.
Design iterations fueled by AI enabled design software could assist in providing the creative teams more options for peer review and early project cost estimation.
Rendering Multiple Options
Realizing early design iterations and options with meaningful design team input quicker earlier in the project’s design phases, can assist in reducing missteps or wasted design soft cost on dead end ideas and concepts. Since in the early design phases of a project, prior to full capitalization, design hours are limited and must be used wisely.
Using innovative AI and machine learning to assist the design teams early progress can aid in eliminating design time waste and reduce concepts that do not support the overall theme or story of a new project.
Realtime Cost Estimating
Realtime cost estimating has been on my radar and project design wishlist for years. Currently, design teams work for several months to generate early design drawings and documents at specific intervals and milestones. At the end of those design phases an extensive cost estimating effort is performed by the contractor. This effort can take weeks to formalize an early project cost estimate used to compare against the project’s overall cost and budget.
The design time and project schedule wasted on this effort – potentially on project scope that may eventually get removed in a later value engineering effort – is wasteful. If we could harness the power of AI enabled realtime cost estimating would greatly assist the design team’s time and design budget. On the backend, it would provide the project owner’s finance team more accurate metrics to the project’s cost.
Reduced Design Schedules
Theme park project’s design schedules are more extensive and longer in duration than typical, real-world commercial projects. We have three additional early design phases – Blue Sky, Concept, and Feasibility – prior to reaching the Schematic Design Phase, where most commercial projects begin their design.
Theme park projects such as new lands or entire new theme parks can take 5 – 10 years to design and construct. For theme park projects of this size, our design phases alone run between 2 to 5 years depending on the complexity of the project.
Reduced Design Risk
Theme park design teams, like design teams working on real-world commercial projects, are constantly working to reduce their design risk via Design Risk Assessments (DRA). Per the Business Dictionary, Design Risk is defined as “The process of determining the probability of design flaws or engineering errors relating to a particular product or service affecting the cash flow, reputation, or other aspect of an organization. Design risk assessments help to identify and resolve potential problems before a product is manufactured and sold.”
Regarding the built environment, the definition of DRA is similar. If you replace the word ‘product’ with, for example, ‘facility’ or ‘project’; the meaning holds true. The overarching theme, and reason to perform an early DRA, is to predict future potential design issues or unknown issues that will affect the final design.
A DRA empowered and enhanced by Artificial Intelligence to be more predictive given a defined set of project standards, program requirements, and design requirements could reduce latency in the design schedule and reduce the opportunity for design flaws or undefined project scope in the project’s design contract documents.
Fully Integrated Designs
A fully integrated and coordinated set of design contract documents and drawings is the goal of every project team, regardless if it is a new residential project, a commercial project or theme park project. A fully coordinated and integrated design – enabled by AI – incorporating all of the owner’s design requirements, all of the creative team’s design concepts, and meets all regulatory legal requirements is the ultimate goal.
Unclear or missed scope not captured in the project’s contract documents – drawings, calculations and specifications – yields expensive changes in the field during construction. AI-enabled design can reduce project cost overruns and time lost during implementation in the field.
Getting Designs to Market Faster
Infusing AI and machine learning into our design phases could potentially assist in reducing that timeframe, make the designs more fully integrated, could assist with design change latency, and provide quicker ideation or options for review and estimating. Shedding 1 to 2 years off a theme park project’s design phase could potentially save several millions of dollars in soft cost.
Improved Permitting and Field Inspections Process
Similar to the milestone efforts required for project cost estimating prior to permitting and construction, machine learning could assist on the backend to achieve the proper multiple design reviews required by building departments, fire marshals, various state agencies, etc. prior to achieving the permits for construction.
AI could assist and improve the permitting process and post-permit the field inspection process required during milestone efforts on job sites curing construction. Currently, when a project design is completed the design manager will submit the thousands of sheets of drawings and engineering calculations to the building department for review – to ultimately achieve the permit for the commencement of construction. Infusing AI into that review process could potentially reduce the weeks of review, to potentially days or hours.
AI Will Improve Theme Park Guest Experiences
AI technology can help theme parks create personalized experiences for visitors by analyzing their preferences and behaviors. This could include customized ride experiences, unexpected experiences in the area development or outdoor spaces between attractions, personalized food and beverage recommendations, unique interactions during overnight stays at themed resorts, and tailored entertainment options.
Theme parks rely heavily on their rides and attractions, which need to be constantly maintained and repaired. AI can help optimize maintenance schedules by analyzing data on the performance of rides and predicting when they will need maintenance before any issues arise. Currently many theme parks use the Maximo system to track mechanical parts, etc. AI could integrate and expand the capability of these types of systems to inform when specific parts need to be replaced based on their utilization curves.
One of the biggest complaints of theme park visitors is waiting in long queues. AI technology could help optimize queue management by analyzing real-time data on wait times, ride capacity, and visitor flow, daily park attendance numbers in realtime, and adjusting queue lengths and ride operation accordingly. Many systems have attempted to perform these efforts, such as FastPass and queue lounges, however though millions of dollars were invested they never actually diversified crowds within the parks as promised and Guests became subservient to and limited to only a few attractions per day.
AI-powered virtual assistants could be integrated into the theme park experience, providing visitors with information on wait times, attraction availability, and park amenities. These virtual assistants could also use natural language processing to answer visitor questions and provide personalized recommendations. Think of this as being a virtual Guest Relations that operates in realtime where issues or concerns can be addressed immediately without sitting on a phone call or taking time out of your daily visit to a theme park to wait in line at Guest Relations.
AI can enable real-time tracking of visitor movements throughout the park, which could help park operators optimize crowd flow, monitor visitor behavior, and ensure guest safety. This system can be tied into the overall resort’s reservation system to further analyze attendance numbers in the future to more accurately predict queue wait times, available hotel and restaurant reservations, and assist in employee staffing requirements to better fluctuate with Guest crowd demands.
✳️ Read more about theme park Design Management Processes
AI-powered augmented reality (AR) could be used to enhance the theme park experience by overlaying digital content onto the physical environment. This could include interactive games, enhance queue experience/pre-show Scene One experiences, scavenger hunts, and virtual overlays on rides and attractions. This technology could be utilized for the personalization of Guests visits as noted above.
AI could help theme parks implement more accurate dynamic pricing models, which adjust ticket prices based on real-time demand and other factors such as weather conditions and special events. Though this currently is part of many theme parks operational and fiscal models, Artificial Intelligence could level-up the metrics to be more accurate and more predictive.
Theme parks consume a significant amount of energy, particularly during peak times. AI could be used to optimize energy usage by analyzing real-time data on weather conditions, visitor traffic, and energy usage, and adjusting operations accordingly. Most of the top theme park operators currently use multiple types of energy management systems for their HVAC systems, their water feature filtration systems, their backup generators, etc., AI could enhance the power, chilled water, natural gas, etc. load studies to further refine and aid in defining utility efficiencies.
AI-powered autonomous vehicles could be used to transport visitors throughout the park, reducing congestion and improving efficiency. These vehicles could also be used to transport goods and supplies around the park or Guests to and from the parking lots. Autonomous vehicles may be incorporated into the themeing or show aspect of particular lands as part the storyline or immersive experience.
AI could be used to monitor the environment in and around theme parks, analyzing data on air quality, noise levels, enhanced security efforts, and other environmental factors. This could help park operators identify and address potential environmental issues before they become problems.