Industry executives and experts share their predictions for 2025. Read them in this 17th annual VMblog.com series exclusive.
By Greg Porter, Principal Solutions Architect, Sev1Tech
In 2024, we
saw the use of digital twins surge across industries, with organizations
leveraging the technology to streamline operations, maximize efficiency and
optimize decision-making. This trend will not slow down
in 2025-the global market for digital twins is expected to grow at 60%
annually over the next five years, reaching $73.5 billion by 2027.
As defined
by the Digital Twin
Consortium, a digital
twin is a virtual representation of real-world entities and processes,
synchronized at a specified frequency and fidelity. Powered by domain knowledge
and real time data, digital twins provide a holistic, end-to-end view of data
across an entire organization.
Digital
twin capabilities are evolving, starting to fuse with GenAI to create Multi-agent
GenAI Systems, known as MAGS. Composed of multiple interacting GenAI-based
agents, MAGS work together to solve operational
challenges across industries, driving increases in production throughput and reducing
maintenance planning time.
In the near
future, we can expect to see the complete
automation of AI agents inside of MAGS, allowing the agents to build, sustain
and drive their own digital twin, with companies being able to update those agents
as new data and data sources come in.
A key
difference between traditional ML predictive tools and MAGS is the closed loop
that has connectivity back to real-time, real-world data to enable automated
decision-making.
In 2025, more
government and commercial organizations will utilize MAGS and digital twins to
simulate operations more efficiently and cost effectively. As such, it will be imperative
they take the steps to effectively manage and leverage the technology for
success, including investing in the education of personnel operating these
platforms and pursuing strategic collaboration with industry partners to ensure
proper deployment and utilization.
MAGS Will Drive
Sustainability
In the
coming year, we will see more organizations adopt MAGS and digital twins to
advance sustainability initiatives, utilizing the technology to create greener
systems and decrease utility use.
While some organizations
use traditional machine learning tools to predict energy consumption
with mathematical algorithms, the incorporation of MAGS will enable organizations
to predict when resources will
be used or shut down and drive automated actions. For
example, MAGS will be able to detect when an organization doesn’t have any
employees in a certain area of its building, shutting down lights and air conditioning
to conserve energy.
Interoperability
Will Empower Government Operations
Government
agencies will maximize the benefits of digital twins through focused
investments in advancing interoperability. Across the federal landscape, technological
siloes lead to repetitive work and development of duplicative capabilities across
agencies.
Even within
the agencies themselves, there may also be numerous vendors – each with their
own digital twins and assets, working on their component of a complex mission
simultaneously.
Interoperability
will allow agencies to exchange critical data with other agencies and with the
different vendors in their own ecosystems. Sharing capabilities and the
resulting findings will save agencies and other organizations time and money.
We
expect to see guidelines from entities such as The Digital Twin Consortium and the
Office of Science and Technology Policy’s NITRD
National Coordination Office that aim to address digital twin interoperability
and optimize agency use in the coming year.
AI Policy
Will Determine Digital Twin Success
Forthcoming
AI legislation will have a significant impact on digital twin technology in
2025 as genAI is utilized through MAGS.
AI is becoming
more powerful by the day, with new frameworks and chips running larger and more
advanced models. A certain level of regulation is necessary to ensure ethical
use and privacy. However, highly restrictive AI policies risk limiting the
technology to little or no effectiveness.
A great
example of this lies within the healthcare sector. Physicians and researchers often
create digital twins of patients to assist in biometrics, predictive cell
changes and to inform clinical decision-making. If regulations are enacted that
limit the use of AI data collection and AI-driven tasks, it will render the
digital twin of that patient useless.
A
balanced approach to AI governance will promote the responsible use of AI and transparency,
while also empowering IT modernization and allowing MAGS and other AI-infused
applications to continue transforming the way citizens live, work and engage
with critical services.
2024 saw
a significant increase in digital twin adoption, reflecting organizations’ push
to remain agile and responsive to the demands of the federal and commercial
landscapes. With the introduction of MAGS, increased focus on interoperability
and strategic AI governance, 2025 will be the year that organizations are able
to fully understand, manage and leverage digital twin technology effectively
for mission success.
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About the Author
Greg Porter is the Principal Solutions Architect at
Sev1Tech. He has been with the company since October 2021, leading the
Artificial Intelligence team as well as the company’s Digital Twin and Digital
Thread efforts. He is also a Steering Committee member of the Digital Twin
Consortium. For over 12 years, Greg Porter has been a noteworthy leader in the
IT industry. Prior to Sev1Tech, he was a Senior Systems Architect at Geocent,
leading data analytics for logistics and Hadoop cluster projects, and Senior
Big Data Administrator at Honeywell FM&T, where he was responsible for Big
Data infrastructure design, configuration, installation, and security. Greg
Porter has been honored with multiple Innovator of the Year awards for his
contributions to Sev1Tech and formerly, Geocent. He holds a master’s degree in
Data Analytics from Western Governors University.
