This Month's Latest Tech News in Richmond, VA - Wednesday April 30th 2025 Edition

Richmond's tech scene this April is marked by rapid startup growth, high-profile funding rounds, and a thoughtful community approach to emerging technologies.

Local accelerators such as Lighthouse Labs continue building momentum, supporting diverse ventures from fintech to workflow software, while prominent raises - like SpecterOps' $75M Series B and Qnovia's $16M for pharma innovation - reflect Virginia's expanding pipeline across AI, cybersecurity, and healthcare according to Virginia Business.

Yet, regulatory headwinds are never far behind: although Virginia's governor vetoed new AI guardrail legislation, experts insist AI regulation remains “inevitable,” pushing local leaders to prioritize responsible governance and school districts to form dedicated AI task forces.

As Dr. Shonda Harris-Mohammed put it,

“I do not want our students to have a higher level of knowledge than the teacher in the classroom. I want it to be a partnership and to learn and grow together about things that are new.”

Meanwhile, evolving privacy standards are also in the spotlight with the recent $51.75M Clearview AI biometric privacy settlement, underscoring the need for vigilance and creative compliance for area startups.

Get a full breakdown of the settlement's implications for data practices from Regulatory Oversight's analysis of the Clearview AI biometric privacy settlement and learn how Richmond's schools are proactively managing classroom AI with a task force as reported by WTVR CBS 6 coverage on Richmond public schools' AI task force.

As opportunity and caution remain closely balanced, Richmond illustrates how innovative ambitions can coexist with careful stewardship in a dynamic tech climate.

Owens & Minor is setting a new standard in healthcare logistics by launching two cutting-edge, AI-enhanced distribution centers in 2025 - one in West Virginia, now operational, and another in South Dakota opening this spring.

These facilities will leverage advanced automation, robotics, and augmented reality (AR) to streamline inventory management and make order fulfillment more efficient for Owens & Minor's Products & Healthcare Services division.

According to Andy Long, EVP and CEO of Products & Healthcare Services,

“Over the past two years, our P&HS teammates have worked creatively and diligently to identify areas where technology investments, operational upgrades, and new approaches to how we do business could have a meaningful impact for our customers.”

Part of a broader investment in technology, these centers mark a two-year innovation initiative focused on improving customer experience and strengthening supply chain resiliency for thousands of healthcare providers.

Notably, the South Dakota facility will debut AR-guided order picking, while West Virginia's hub excels in robotics-driven efficiency. To further bolster their capabilities, Owens & Minor has also partnered with Google Cloud, leveraging its Vertex AI platform to enhance their QSight® clinical inventory system and provide customers with real-time, predictive analytics.

For a comprehensive breakdown of the new center capabilities, see the table below:

Location	Status	Key Technology	Purpose
West Virginia	Open	Automation & Robotics	Streamline inventory & order fulfillment
South Dakota	Spring 2025	Augmented Reality (AR)	Enhance order picking process

These investments underscore Owens & Minor's commitment to innovation as they support healthcare delivery from hospitals to homes.

For further details, explore the official press release on Owens & Minor's major innovations in healthcare logistics, a comprehensive update in Healthcare Purchasing News' coverage of the new technology rollouts, and insights into their strategic tech partnerships via the Google Cloud partnership announcement.

Meta has unveiled its highly anticipated standalone AI app powered by the advanced Llama 4 model, aiming to set a new benchmark for consumer AI assistants. The Meta AI app, available now on iOS and the web, distinguishes itself with a seamless, voice-first interface, personalized responses, and integrated features for image generation and editing - all designed to get to know users' preferences and context over time.

Llama 4, particularly the Scout and Maverick models, deliver state-of-the-art performance in coding, reasoning, and multilingual capabilities, outpacing rivals like GPT-4o and Gemini 2.0 Flash-Lite in benchmarking.

Meta's app not only supports natural back-and-forth conversations but introduces a Discover feed for sharing and remixing AI prompts, and extends functionality to Ray-Ban Meta glasses through cross-device integration.

As noted by CEO Mark Zuckerberg, the goal is to make AI

"a constant, helpful presence throughout daily life,"

advancing conversational, multimodal engagement for nearly 4 billion users globally.

The launch also coincides with Meta's LlamaCon developer event, highlighting a broader open-source push and positioning Meta as a major competitor against OpenAI and Google in the consumer AI space.

For a technical comparison of Llama 4's leading models, see the table below:

Model	Active Parameters	Experts	Context Window	Benchmark Standing
Llama 4 Scout	17B	16	10M tokens	Outperforms Gemma 3, Gemini 2.0 Flash-Lite, Mistral 3.1
Llama 4 Maverick	17B	128	-	Beats GPT-4o, Gemini 2.0
Llama 4 Behemoth (in training)	288B	16	-	Outperforms GPT-4.5, Claude Sonnet 3.7, Gemini 2.0 Pro (STEM)

To learn more about the app's features and platform strategy, visit the official Meta AI app announcement, see independent coverage on Meta's consumer AI impact at VentureBeat, or read analysis on Meta's AI rival strategy at CNN Business.

Microsoft is taking a careful, data-driven approach to its massive AI infrastructure expansion, announcing a pause or slowdown on select early-stage data center projects worldwide - including a high-profile $1 billion initiative in Ohio.

This recalibration comes amid explosive demand for AI and cloud services that has doubled Microsoft's data center capacity over the past three years, outpacing the industry's ability to keep up with power, supply chain, and construction timelines.

Financial analysts underscore that the move signals not a retreat from AI, but a shift toward capital efficiency after years of aggressive growth, as Microsoft plans to spend over $80 billion globally on AI data centers in fiscal 2025 alone.

According to the Associated Press, the pause also reflects a changing partnership with OpenAI and the complex realities of energy sourcing, with plans underway to revive nuclear power at Three Mile Island to support new data center hubs in Ohio and Virginia.

Noelle Walsh, President of Microsoft Cloud Operations, emphasized the scale of the challenge:

“In recent years, demand for our cloud and AI services grew more than we could have ever anticipated and to meet this opportunity, we began executing the largest and most ambitious infrastructure scaling project in our history. Any significant new endeavor at this size and scale requires agility and refinement as we learn and grow with our customers. What this means is that we are slowing or pausing some early-stage projects.”

Industry research, such as analysis by UBS on Microsoft's data center slowdown, suggests these changes are a strategic reset, not a cooling of AI momentum, with a forecasted 125% increase in leased data center capacity still projected for FY25.

Broader data from XYZ Reality's April 2025 Data Center Rundown details that Microsoft's caution echoes a sector-wide trend, as hyperscale cloud providers balance massive capital investment with the practicalities of power, permitting, and global economic headwinds.

Economists at the Richmond Fed are taking a nuanced view of artificial intelligence's (AI) long-term impact on productivity and economic growth. Despite eye-catching forecasts - such as Goldman Sachs predicting a $7 trillion uplift to global GDP and up to 3.4 percentage points higher growth in developed nations - the evidence suggests a weaker link between rapid technology adoption and measured productivity gains.

As highlighted in The Productivity Puzzle: AI, Technology Adoption and the Workforce, workforce demographics, specifically the age and experience of workers, appear more influential for productivity than just rolling out new tech.

Echoing economist Robert Solow's famous observation,

“you can see the computer age everywhere but in the productivity statistics,”

recent Richmond Fed analyses stress that the economic reaction to AI is driven as much by news and expectations - so-called “TFP news shocks” - as by tangible advances.

This means announcements regarding AI, even before technologies mature or spread, spark wealth effects that boost consumption and investment, as detailed in What Can News Shocks Tell Us About the Effects of AI?.

Yet, for AI to drive significant aggregate productivity growth, it must reach far beyond the tech and intellectual property sectors - sectors that currently comprise only 13-15% of GDP. According to Richmond Fed researchers,

“even if AI diffuses beyond IPP, expected impact on aggregate productivity is moderate.”

For a breakdown of major institutional forecasts, see the summary below:

Source	Forecast/Estimate (Next Decade)
Goldman Sachs	$7T global GDP increase, 1.5%+ annual US productivity growth
McKinsey	1.5–3.4% annual GDP growth increase (developed nations)
Daron Acemoglu (MIT)	0.07% annual productivity growth increase, 0.9–1.8% GDP growth

To explore in-depth data and sectoral analysis behind these projections, check out What Shapes Productivity Growth? from the Richmond Fed podcast series.

Owens & Minor's latest investments in automation and analytics are reshaping healthcare logistics, marking a significant step forward for the Richmond-based Fortune 500 company in 2025.

With newly enhanced distribution centers in West Virginia - now operational with advanced robotics - and South Dakota - set to open this spring featuring augmented reality order picking, Owens & Minor aims to streamline inventory management, expedite order fulfillment, and elevate customer service for over 4,000 healthcare providers globally.

Andy Long, executive vice president and CEO of Owens & Minor's Products & Healthcare Services segment, emphasized,

“Over the past two years, our P&HS teammates have worked creatively and diligently to identify areas where technology investments, operational upgrades and new approaches to how we do business could have a meaningful impact for our customers.”

These innovations are funded, in part, by a recently upsized $1 billion senior secured notes offering, positioning the company to both enhance its distribution network and finance additional strategic acquisitions.

The table below summarizes the new facility capabilities:

Facility	Operational Date	Key Technology
West Virginia	Open (2025)	Advanced automation & robotics
South Dakota	Spring 2025	Augmented reality for order picking

For more on distribution network upgrades, see the Becker's Hospital Review coverage of Owens & Minor distribution site enhancements, comprehensive insights on digital transformation in healthcare supply chains at Owens & Minor's April 2025 press release, and the company's financial strategy as detailed in the MassDevice report on their $1B capital raise.

Richmond Public Schools (RPS) are moving to proactively address the opportunities and challenges presented by artificial intelligence in education, as the school board debates the formation of an AI task force focused on classroom integration and ethical use.

The task force's priorities include establishing clear guidelines for AI tool use, safeguarding assignment integrity, ensuring comprehensive teacher training, and reviewing future policy needs.

Dr. Shonda Harris-Mohammed, chair of the policy committee, highlighted the collaborative spirit behind the initiative:

"I do not want our students to have a higher level of knowledge than the teacher in the classroom. I want it to be a partnership and to learn and grow together about things that are new."

This work aligns with both the district's strategic plan, Dreams4RPS, which emphasizes modern systems and infrastructure, and the statewide momentum spurred by recent executive guidance on AI education.

Notably, the policy under consideration draws on samples from districts across Virginia and is part of a growing movement to invest in training, cybersecurity, and ethical guardrails.

The task force's recommendations are expected to be finalized and presented to the school board by summer, as reported by WTVR CBS 6.

This initiative comes as national attention turns to federal AI education efforts, including a new executive order directing agencies to prioritize artificial intelligence initiatives and educator training in K-12 settings - underscoring Richmond's engagement in a critical conversation for the future of digital literacy.

For additional insights on the federal context, explore the full White House executive order on AI education.

Despite persistent myths about rampant academic dishonesty, recent surveys show that most teenagers are harnessing artificial intelligence as a powerful learning tool, not for cheating.

According to a University of California, Irvine and Foundry10 survey, 69% of teens using AI tools report these technologies helped them learn something new, while less than 6% experienced negative repercussions like conflicts with teachers or parents (Teens are embracing AI - but largely not for cheating, survey finds).

Data from Turnitin's AI detection software supports this narrative: only 3% of more than 200 million student writing assignments reviewed in the last year were largely AI-generated, showing that AI-fueled cheating is far from pervasive and that self-reported cheating rates haven't increased with the rise of generative tools like ChatGPT (New Data Reveal How Many Students Are Using AI to Cheat).

Instead, experts and educators increasingly advocate for reframing the AI conversation from plagiarism prevention to building responsible use and digital literacy skills for the future.

As one Turnitin executive notes,

“What the feedback we're hearing now from students is: ‘I'm gonna use it. I would love a little bit more guidance on how and when so I don't get in trouble, but still use it to learn.'”

With growing adoption across K-12 classrooms - 63% of teachers and administrators say they are incorporating GenAI - education leaders are now focused on creating policies that foster transparency, ethical use, and agency rather than relying on detection tools alone (AI in Education Report: New Cengage Group Data).

A recent University of Richmond study sheds light on the complex risks AI-driven advertising poses to brand trust, especially as generative AI and virtual influencers grow more prevalent in digital marketing.

Researchers found that AI-powered virtual influencers - used by major brands on platforms such as TikTok and in the metaverse - may threaten reputation more than their human counterparts, as consumers often attribute mistakes or misleading information from AI influencers directly to the brand rather than the technology itself.

This aligns with broader industry concerns, where 100% of advertising professionals recognize brand safety and misinformation risks stemming from AI-generated content, and U.S. consumer trust in AI-driven ads has dropped from 50% to 35% in the last five years.

At the same time, transparency remains a critical solution: according to a global RWS survey, 62% of consumers would trust brands more if they clearly disclosed their AI use.

The table below summarizes key findings from these studies:

Key Issue	Study/Source	Statistic/Insight
Impact on Brand Trust	University of Richmond / Northeastern Study on AI Influencer Marketing and Brand Trust	AI influencers may damage trust more than human influencers - consumers blame brands directly for AI errors.
Consumer Perception	Basis AI Advertising Report on Brand Safety, Consumer Trust, and Legal Concerns	U.S. consumer trust in AI ads fell to 35%; 66% of adults uncomfortable with AI-generated ads.
Transparency Boosts Trust	RWS Research on Global Consumer Trust and AI Disclosure	62% of global consumers trust brands more when AI use is clearly disclosed and explained.

“Organisations must recognise their accountability for the actions of AI-powered virtual influencers, as these directly affect brand trust.” - Study conclusion

For Richmond's marketers and tech leaders, these findings highlight a pressing need for strong oversight, clear disclosure, and human involvement to maintain authenticity and consumer confidence in an evolving AI-driven landscape.

Richmond's legal sector is witnessing a major transformation as artificial intelligence (AI) becomes integral to daily practice, with tools reshaping document review, research, and client engagement.

AI-powered solutions now cut due diligence time by up to 70% and offer predictive analytics - platforms like Pre/Dicta achieve 86% accuracy forecasting judicial outcomes - delivering operational and strategic advantages for local firms.

Despite these advancements, recent surveys reveal that only 34% of in-house legal departments are actively using generative AI for tasks such as legal drafting, hampered by budget and data challenges, as detailed in the 2025 EY Law General Counsel study.

AI's role is especially powerful in automating “low value” administrative work, allowing lawyers to focus on high-value client counseling and strategy - an evolution explored in LexisNexis's insights on legal workflows.

However, local firms must ensure robust oversight to address ethical risks like data privacy and AI-generated errors; a recent incident saw a federal judge sanction a firm for trusting inaccurate AI-generated legal citations, reinforcing the necessity of human review.

As summarized by Virginia Lawyers Weekly:

“AI is not just enhancing legal processes - it is fundamentally reshaping them. This shift enables law firms to improve operational efficiency, increase accuracy, and deliver more strategic, client-centric services in the modern era.”

For a deeper dive into the pace of adoption, productivity gains, and ongoing concerns in Richmond's legal tech landscape, listen to the recent panel discussion in the AI Lawyer Talking Tech podcast.

The table below illustrates key statistics on AI's impact across legal practices:

Use Case	AI Impact / Statistic
Document Review Speed	Up to 70% reduction in due diligence time
Productivity Gain (US Lawyers, annual)	266 million hours saved
AI Adoption (In-house Legal Teams)	34% active use
Predictions Accuracy (Judicial Outcomes)	86% (Pre/Dicta platform)

Elon University's A.I. & E.T. Club is rapidly becoming a regional catalyst for artificial intelligence engagement and workforce readiness, offering platforms for students to experiment, collaborate, and apply AI skills across disciplines.

Backed by an Elon Innovation Grant, the club - founded by Joshua Mason and Aaron Satko - hosts creative events like AI image generation competitions and helps connect students with state-wide AI programs.

Their upcoming collaboration with the Data Nexus for DataFest 2025 underlines their commitment to experiential learning. In the words of Mason:

“We both wanted to create a space for like-minded people. We like learning about new technologies, and it's hard to find people like us around campus.”

Elon's broader support for AI integration is evident through initiatives such as the AI Pedagogy Challenge, which incentivizes innovative, ethical classroom uses of AI, and community workshops led by the Center for Design Thinking, teaching practical prompt engineering and responsible tool adoption.

The university's AI club sparks conversations around emerging technology, while the AI Pedagogy Challenge incentivizes faculty creativity and responsible AI use.

These efforts are complemented by hands-on, interdisciplinary AI workshops that enhance academic and career readiness, reflecting Elon's dedication to equipping tomorrow's workforce for the realities of an AI-driven world.

Richmond's emergence as an AI and tech epicenter is the result of purposeful community engagement, educational innovation, and collaborative leadership. The city's dynamic growth is driven by initiatives such as AI Ready RVA, whose mission to cultivate AI literacy and foster economic development is reinforced by inclusive events, business partnerships, and a robust focus on both K-12 and workforce readiness.

Grassroots efforts are yielding tangible results, as highlighted by transformative achievements among low-income students in Richmond's public schools - students supported by programs like UBU 100 are not only outperforming expectations but also inspiring new models for equitable community uplift (read more about Richmond's academic advances).

The city's policy and educational landscape are rapidly evolving to prioritize AI integration, from federal alignment to Virginia's 2027 standards update and teacher training, ensuring that emerging talent is prepared for the region's growing tech workforce (see the latest Virginia Education Update for details).

These collective efforts - supported by local government, nonprofits, and academic leaders - underscore Richmond's unique ability to balance technological progress with social responsibility, making it a model for cities navigating the promise and responsibility of the AI era.