Modeling Tomorrow in Practice: Generative AI Assistants and Health Wearables in IMPLAN

INTRODUCTION

Emerging technologies are reshaping industries in profound and rapidly evolving ways, and the need to accurately estimate their economic implications is more important than ever. In “Modeling Tomorrow: How to Classify Emerging Technologies in IMPLAN,” we explored 12 technologies highlighted in a Wall Street Journal article, providing NAICS and IMPLAN Industries to accommodate new innovations inside today’s modeling framework.

This article builds on that foundation by moving beyond Industry classification to modeling economic impacts. Here, we walk through two of the most widely applicable examples, Generative AI Assistants and Health Wearables, offering step-by-step guidance on how to set up and interpret IMPLAN analyses for each. These use cases should resonate with IMPLAN users because they represent fast-growing sectors where analysis is already being requested by economic developers, policymakers, and corporations.

FROM NAICS TO IMPLAN INDUSTRIES

In the “Modeling Tomorrow” article, we used IMPLAN’s Industry Search to map emerging technologies to IMPLAN industries. Based on this, we will anchor our analysis on several industries:

• Industry 410: Software Publishers
• Industry 46: Construction of New Manufacturing Structures
• Industry 300: Electromedical and Electrotherapeutic Apparatus Manufacturing for health wearables

USE CASE 1: GENERATIVE AI ASSISTANTS

BUILDING THE IMPLAN PROJECT

Let’s begin by creating a new Project in IMPLAN and selecting Tennessee as our model Region. This, combined with our data year selection, will determine the data set used for all economic relationships in the model.

To set up the Event and run our analysis, we’ll follow these steps:

• Click Add to Impacts.
• Create an Industry Employment Event.
• Select IMPLAN Industry 410 using the NAICS search tool.
• Enter 120 jobs as the Event value since that’s our known change. Alternatively, if Gig City provides output—e.g., new annual revenue—we should use an Industry Output Event.
• Set the Dollar Year to 2026.
• Run the analysis by dragging the Event to our Group, and then clicking Run.
   

INTERPRETING THE RESULTS 

On the Results screen, click the Summary dropdown menu and click Simplified Overview. The results for Gig City’s expansion show $34 million in labor income and $61.5 million in value added contributions, reflecting the high-skill nature of tech employment. These results include indirect and induced effects that capture additional jobs created at suppliers, and within the broader economy as new wages circulate beyond Chattanooga. Together, these results give Gig City AI a credible estimate of the total impact of adding 120 positions.

USE CASE 2: HEALTH WEARABLES

Health wearables like smart watches and rings can now measure hypertension, sleep apnea, diabetes, and other chronic conditions. As a result, they are becoming central tools in remote health monitoring and virtual care delivery. To illustrate how IMPLAN models this activity, consider Scenic Signal, a fictional medical technology company developing FDA-cleared smart rings. The firm is exploring construction of a new manufacturing facility, representing an $80 million capital investment and 300 ongoing jobs.

The local economic development organization wants to understand one-time construction impacts and the recurring operational impacts of hosting this facility in their region, making this a natural two-phase IMPLAN analysis.

MODELING CONSTRUCTION AND OPERATIONS SEPARATELY 

Because construction is a temporary activity and operations are ongoing, it is best practice to model these phases separately: 

1. Construction is captured using Industry 46: Construction of new manufacturing structures.  
2. The operations phase is modeled using Industry 300, with employment or output entered as the Event value. (Although wearables resemble consumer electronics, their regulatory status and clinical applications place them squarely within medical manufacturing.) 

This separation keeps short-term and long-term effects distinct and easier to interpret.

BUILDING THE PROJECT

For the construction phase, create an Industry Output event in Industry 46 and enter $80 million for the event value. After dragging the Event to the Construction Group, run the analysis to obtain one-time construction impacts such as jobs, labor income, and tax revenues associated with building the facility.

For the operations phase, create an Industry Employment event for Industry 300 and enter 300 jobs for the event value. The model captures ongoing annual impacts, including supplier purchases, labor income, and induced effects arising from household spending by employees at Scenic Signal and its suppliers.

Notice we assume that the construction and operations will be in the same year. Because of this, we wouldn't need to use different groups for these events. The events have the same Data Year and Dollar Year and could be placed in the same group. We use different groups for transparency and organization purposes. In addition, it is important to note that if construction were occurring in a different year than operations, the Data Year and/or Dollar Years may need adjusting to reflect that. 

Taken together, these two phases provide a comprehensive picture of both the short-term construction boom and the long-term manufacturing footprint associated with Scenic Signal’s investment.

INTERPRETING THE RESULTS 

Construction projects have a surprisingly broad impact on the economy, affecting everything from transportation to healthcare while employees are on the job. On the Results screen, click the Employment tab for a nuanced view of Scenic Signal’s construction impact. To see the impacts of just the construction:

1. Using the Group Name filter, select ‘Construction (2024),’ and then click the circular refresh button in the upper-right corner.
2. In the legend for the Top 15 Industries bar chart, click 1 - Direct and Row Total to unselect those series, leaving only 2 - Indirect and 3 - Induced showing.

The chart highlights construction’s wide-ranging impact, with indirect jobs spread across the supply chain. This includes industries like truck transportation, wholesale, and concrete. Induced effects arise from consumer spending by newly employed workers, supporting jobs in full- and limited-service restaurants, hospitals, and retail industries, among others.

FORWARD LINKAGES: MODELING PRICES INCREASES IN HEALTH WEARABLES

Traditional IMPLAN analysis focuses on backward-linked effects, or those that measure how changes in final demand propagate upstream through the supply chain. A new feature called Forward Linkages enables users to analyze downstream, “cost-push” effects. Forward Linkages represents an entirely different dimension, allowing analysts to explore how price changes in input industries ripple through the sectors that rely on them.

To illustrate this, consider a 5-percent increase in the price of health wearables. Scenic Signal may face rising costs due to component shortages or regulatory changes. Downstream users like telehealth providers, outpatient care facilities, and health plans rely on these devices to deliver remote health monitoring and chronic care. Using Forward Linkages, IMPLAN can model how the price increase affects these downstream industries, assuming no change in the amount of health wearables purchased.

From the IMPLAN home screen, select the Price Change (Cost-Push Guide). Then, follow the prompts to select a Sub-National US Region and then Tennessee. After selecting the region, search for “electromedical and electrotherapeutic apparatus” to see all the commodities in that category. All of the related commodities fall under IMPLAN Commodity Code 3300.

After advancing to the next screen, confirm that % Change in Price is selected and enter “5.” IMPLAN will then provide an overview of your analysis set-up before prompting you to create a project name. 

On the results screen, click Output to see a detailed overview of the affected industries. We should expect physicians offices to be most impacted by an increase in the cost of health wearables, followed by a range of other healthcare industries.
 

Our analysis triggered a cost-push ripple effect through the multiple industries, estimating how downstream output, value added, and employment adjust to absorb increased costs. 

Forward linkages analyses are especially valuable for sectors like healthcare, where cost increases can influence access, utilization, and organizational budget planning. When combined with the more familiar backward-linked analysis of construction and operations, forward linkages provide a richer, more complete view of the economic role of emerging technologies, like health wearables.

Note: Although health wearables fall under the broader commodity category of electromedical and electrotherapeutic apparatuses, they differ from many traditional devices in this group because they are worn directly on the body and used continuously by consumers. While this distinction does not change how IMPLAN structures the Forward Linkages analysis, it may influence how heavily certain healthcare or digital‑health industries rely on these products in practice, so users should interpret downstream impacts with that nuance in mind.

CONCLUSION

The use cases on generative AI and health wearables demonstrate how emerging technologies can be modeled confidently and accurately using IMPLAN’s existing Industry scheme. By pairing NAICS classifications with IMPLAN’s modeling tools, users can produce credible impact analyses even for cutting-edge technologies. Furthermore, the Forward Linkages feature allows analysts to extend their work downstream, capturing cost-push effects that traditional analysis cannot. Collectively, these tools offer a comprehensive framework for evaluating the economic footprint of innovations that are shaping our lives.

RELATED ARTICLES

Forward Thinking: A New Dimension in Impact Analysis

Modeling Tomorrow: How to Classify Emerging Technologies in IMPLAN

NAICS to IMPLAN Industry Search

REFERENCES

Joanna Stern, Nicole Nguyen & Christopher Mims, “Tech That Will Change Your Life in 2026,” The Wall Street Journal, December 26, 2025.

Written February 18, 2026