Spotlight On: Liz Krugliak, Office Leader, RSM Pittsburgh
Key points:
- • AI is creating new opportunities for middle-market productivity and growth.
- • Data governance and cybersecurity are critical to responsible AI adoption.
- • Workforce strategies increasingly emphasize adaptability, judgment, and digital skills.
September 2026 — In an interview with Invest:, Liz Krugliak, Pittsburgh office leader at RSM US, the leading provider of assurance, tax, and consulting services for the middle market, discussed the opportunities and risks shaping middle-market businesses, including artificial intelligence, cybersecurity, regulatory change, and workforce development. “We want to know what keeps business owners up at night, where they see the organization heading, and how we can support that direction,” Krugliak said.
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What opportunities and challenges are middle market businesses facing in today’s economic environment?
Middle market businesses today face a unique combination of challenges and opportunities. While economic uncertainty, higher capital costs, workforce shortages, supply chain shifts, and geopolitical volatility continue to pressure margins, many organizations are using these conditions as a catalyst for innovation and transformation.
One of the most significant opportunities facing middle market organizations today is leveraging AI to drive productivity, resilience, and growth. The biggest challenge is moving beyond isolated pilots and building the data, governance, talent, and operating models necessary to scale AI across the enterprise. The organizations that solve that challenge will create a meaningful competitive advantage in an increasingly complex economic environment.
However, the challenge is no longer whether AI works. The challenge is scaling it effectively. Many middle-market organizations have achieved success with isolated use cases but struggle to move from pilot programs to enterprise-wide transformation. Data quality, legacy systems, cybersecurity concerns, governance requirements, and workforce readiness remain the most significant barriers to adoption. Organizations are discovering that successful AI implementation requires much more than technology investment; it requires clear business objectives, strong data governance, change management, and alignment between leadership, operations, and technology teams.
Ultimately, the middle market is at an inflection point. The economic environment is demanding greater productivity, agility, and resilience. Organizations that successfully combine operational discipline with strategic investment in AI and digital transformation will be better positioned to drive growth, create enterprise value, and strengthen their competitive position.
AI is a tool in the toolbox. Businesses still need to validate the information it provides and determine whether the investment will generate an appropriate return. RSM helps companies evaluate how technology can improve manufacturing, operations, finance, and accounting functions. The broader challenge is creating efficiencies without placing undue pressure on margins. This is a long-term investment process, and companies need a clear understanding of how the technology will support their operational priorities.
How can companies adopt AI responsibly while protecting governance, security, and regulatory compliance?
A responsible AI strategy starts with strong governance. Organizations should establish clear ownership of AI initiatives, define acceptable-use policies, create approval and monitoring processes, and implement oversight mechanisms that promote accountability, transparency, and risk management. As AI becomes increasingly embedded in critical business processes and decision-making, executive leadership and boards must understand not only the potential benefits of AI, but also how outputs are generated, validated, and governed.
Equally important is a solid foundation of data security and data governance. AI systems are only as reliable as the data that powers them. Leading organizations focus on strengthening data quality, protecting sensitive information, establishing appropriate access controls, and ensuring AI solutions align with cybersecurity and privacy requirements. This becomes even more critical as companies deploy generative and agentic AI capabilities that interact with large volumes of enterprise data and customer information.
For many middle market organizations, particularly those operating across multiple countries, the challenge extends beyond technology. Governance and compliance obligations often span numerous regulatory jurisdictions, each with its own requirements related to privacy, data sovereignty, financial reporting, and industry-specific regulations. As a result, companies must evaluate AI through an enterprise-wide lens, considering the regulatory and operational implications across their entire global footprint.
At RSM, we help clients navigate this complexity by understanding their unique business objectives, compliance obligations, and risk profile. We work with organizations to identify potential areas of exposure, strengthen governance frameworks, and evaluate where AI and emerging technologies can support strategic priorities, enhance operational performance, and accelerate growth. Because every organization has different goals, systems, and regulatory requirements, there is no one-size-fits-all solution. Successful AI adoption requires a tailored approach that balances innovation with responsible governance, security, and compliance.
Why is data quality so important when businesses begin implementing AI?
Data quality is the foundation of every successful AI initiative. AI systems can only generate insights, predictions, and recommendations based on the information they are given. If the underlying data is inaccurate, incomplete, inconsistent, or outdated, the outputs will be unreliable regardless of how sophisticated the technology may be. RSM’s Middle Market AI research identified data quality as the most commonly cited barrier to successful AI adoption, ranking ahead of security concerns, legacy systems, and skills gaps.
At RSM, we often encourage clients to view AI and data readiness as inseparable. Before focusing on advanced AI use cases, organizations should evaluate the quality of their data, establish governance standards, and align their technology investments with business objectives. Companies that build a strong data foundation are significantly better positioned to scale AI, generate trusted insights, and achieve sustainable business value.
How does RSM help clients prepare for changes in tax policy and the regulatory environment?
The pace of regulatory and tax change continues to accelerate, creating both complexity and opportunity for middle market organizations. At RSM, we help clients move beyond simply reacting to changes and instead take a proactive approach to understanding how evolving tax policies, regulatory requirements, and economic conditions may affect their business objectives, operations, and growth strategies.
Our approach begins with helping clients stay informed. Through RSM’s industry, tax, and economic thought leadership, including our middle market research and industry outlooks, we provide insights into emerging trends, legislative developments, and regulatory shifts that may impact businesses. These insights help leadership teams anticipate change, evaluate risks, and make more informed strategic decisions.
Because every organization faces a unique set of business, tax, and regulatory challenges, there is no one-size-fits-all solution. RSM brings together tax, risk, technology, and industry specialists to help clients understand the full impact of change, evaluate strategic options, and position their organizations for long-term growth and resilience.
What should organizations prioritize as cybersecurity and data privacy risks become more sophisticated?
As cybersecurity threats and data privacy risks continue to evolve, organizations should prioritize building a comprehensive risk management strategy that combines strong governance, cybersecurity controls, data protection, and employee awareness across their entire footprint. Today’s threat landscape is no longer limited to external attacks. The rapid adoption of cloud technologies, AI, third-party platforms, and increasingly complex data ecosystems has expanded both the number of vulnerabilities and the potential business impact of a security incident.
The first priority should be data governance and visibility. Organizations need to understand what data they possess, where it resides, who has access to it, and how it is being used. As AI becomes more integrated into business processes, the ability to maintain accurate, secure, and well-governed data is increasingly critical. Strong data governance not only improves cybersecurity resilience but also supports privacy compliance and trusted AI adoption.
Regulatory compliance should be viewed as an ongoing process rather than a one-time exercise. Organizations operating across multiple jurisdictions face increasingly complex requirements related to privacy, data protection, reporting obligations, and industry-specific regulations in a changing world. Companies should continuously monitor regulatory developments, assess potential exposure, and align governance and compliance programs with their broader business strategy.
Finally, organizations should invest in workforce readiness. Technology alone cannot eliminate cyber risk. Employees remain one of the most important lines of defense, and organizations that foster a culture of security awareness, accountability, and ongoing education are often better equipped to manage emerging threats and reduce risk. As new technologies such as generative and agentic AI become more prevalent, employee understanding of secure and responsible usage will become increasingly important.
How are technology and changing expectations reshaping workforce strategies?
Technology and AI are transforming how organizations attract, develop, and retain talent. Today’s workforce, particularly newer generations entering the profession, expects AI and digital tools to be embedded in their daily work experience. As a result, organizations are investing in technologies that automate routine tasks, improve productivity, and allow employees to focus on higher-value work.
However, workforce transformation is about more than technology adoption. Successful organizations are redesigning processes, redefining roles, and helping employees work alongside AI rather than simply training them to use new tools.
As AI makes information more accessible, skills such as critical thinking, communication, collaboration, and professional judgment become even more important. In a client-focused business, employees must be able to understand client needs, interpret information, solve problems, and communicate recommendations effectively. While technology can generate insights, people are ultimately responsible for applying judgment and making informed decisions.
How does the power of being understood shape RSM’s client relationships?
The Power of Being Understood is at the heart of everything we do. While many client relationships begin with an assurance, tax, or consulting need, our goal is to understand the broader story behind the business, where it’s headed, what challenges it faces, and what success looks like for its leaders.
We invest time in getting to know our clients, their management teams, boards, owners, and investors because the best solutions come from understanding what matters most to them. By developing that deeper perspective, we’re able to provide insights that go beyond compliance, helping clients identify opportunities, navigate risks, and make more informed decisions.
At RSM, we don’t view relationships as transactions. We strive to be trusted advisors who grow alongside our clients, supporting them through change, helping them achieve their goals, and providing the confidence that comes from having an advisor who truly understands their business.
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