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Mid-market leaders don’t need hype. You need clarity. Whether you’re exploring use cases, assessing organizational readiness or beginning to build, our AI consulting team works with you to turn strategy into action.
Create a unified AI strategy, with policies to guide experimentation, adoption and risk.
Connect systems and implement effective data management and governance practices.
Access business advisors, engineers and analysts without adding headcount.
Design for responsible use and prioritize use cases grounded in practical value.
Focus on ROI and the right automation for your strategy.
AI isn’t the future. It’s your next move.
Our AI consulting services are built for the mid-market. While other firms push big-enterprise solutions, we focus our AI services on helping growth-focused companies use AI in ways that make sense for their size, culture and systems.
Explore our AI consulting services
Clarify what AI means for your business. From traditional analytics to emerging capabilities like agentic AI, we help you define strategic goals, identify practical use cases, and prioritize initiatives based on ROI and readiness.
Design policies and frameworks to guide adoption and mitigate risk. We assess your data, tech stack and workflows to identify readiness gaps, then help you establish ethical and compliant governance frameworks, so AI adoption remains secure and sustainable.
Activate intelligence tools that accelerate workflow. We assist with custom Copilot builds, LLM integrations and automation projects tailored to your needs.
Need expertise without a full hire? Wipfli provides access to strategists, engineers, analysts and PMO support to fill gaps and drive progress, as well as sprint-based build and deploy options.
Evaluate your data, processes and teams to understand what groundwork needs to be laid. We help you plan responsibly and align AI with broader digital goals.
Turn ideas into action. We facilitate use case design workshops — including generative AI and machine learning — and help you plan for deployment and scale.
Support adoption across your organization. We offer training, communication toolkits and leadership support to help your teams embrace and sustain AI.
Technology alone won’t deliver AI results. Our AI-empowered leadership development program gives executives the training they need to guide strategy and lead an AI-enabled organization with confidence.
Insights and Resources
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Intelligent UI for construction
Learn how construction leaders can use Intelligent UI to access key data quickly in an easy-to-read format.
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How to prepare for CMMC readiness requirements
Many contractors and third-party vendors who work with the Department of Defense (DoD) must comply with Cybersecurity Maturity Model Certification (CMMC) readiness requirements. This set of processes and practices is designed to strengthen organizations connected to the DoD (sometimes informally called the Department of War) against cybersecurity threats by protecting controlled unclassified information (CUI) and federal contract information (FCI). CMMC is currently undergoing a major review, as some key third-party assessment requirements were recently paused by the DoD. However, CMMC rules remain largely in effect and continue to be included in DoD contracts. Here’s what you need to know from a readiness standpoint. What are the CMMC 2.0 requirements? The CMMC 2.0 framework requires that DoD contractors — officially any organization that’s part of the defense industrial base (DIB) — meet certain cybersecurity standards. If you want to do business with the DoD, you’ll need to be CMMC compliant . Maintaining compliance includes identifying whether your company meets one of three CMMC levels based on your degree of exposure to CUI, implementing relevant controls and safeguards and passing regular assessments. Here are the three CMMC levels: Level 1: Foundational cybersecurity for any federal contractors who handle FCI. Level 2: More advanced security standards for organizations that also deal with CUI. Level 3: The highest level of CMMC, meant to protect CUI from advanced threats. Why do you need to achieve CMMC compliance? CMMC exists largely to protect a category of data called CUI. Broadly speaking, CUI is unclassified information that is still sensitive and should be protected for security reasons. All CUI is created by or on behalf of the DoD and is technical information with military or space applications. Where can I find CUI in my organization? Most businesses in the DIB encounter CUI at some point in their work. It can come in many forms like contract documentation, blueprints, schematics, tax information and even some communications. Here are some questions to help you consider where you should look for CUI within your organization: How did we receive the CUI? Who needs to access it in their day-to-day work? Who did we send it to? Where do we store DoD working files and program files? Do we keep hard copies of any documentation for DoD clients or prime contractors? What is the CMMC Phase II pause? CMMC requirements were originally scheduled to be implemented in phases between November 2025 and November 2028. Phase II, which was scheduled to begin in November 2026, would have required that many contractors complete a third-party assessment by a C3PAO (certified third-party assessor organization) to demonstrate Level 2 CMMC compliance to bid on DoD contracts. On July 13, 2026, the DoD announced it was pausing Phase II requirements pending an internal review. That review was scheduled to last for 60 days. However, the pause has continued even after that 60-day period expired in September. For now, other CMMC requirements remain in effect, but DoD contracts cannot require third-party compliance assessments. This leaves self-assessment as the only way to demonstrate compliance. How do you prepare for CMMC compliance? Achieving and maintaining CMMC compliance is a process. Here’s how to get started. 1. Find an advisor to guide you through the process A third-party advisor can help you understand and implement CMMC requirements. This will make the process significantly easier and more successful than trying to do everything internally. Look for an advisor with cybersecurity and compliance experience that’s also a Registered Provider Organization (RPO). An RPO has been security vetted and has also demonstrated a comprehensive understanding of CMMC 2.0 requirements. 2. Conduct a CMMC readiness assessment Next, work with your advisor to assess your organization’s existing cybersecurity preparedness through the lens of CMMC 2.0 compliance. What are you doing right and where are the gaps in your current safeguards or controls? Part of this assessment will be determining how much CUI your organization has in its possession. This understanding will allow you to define your organization’s scope, supporting eventual representations to the government that no CUI data exists outside of it. 3. Implement additional governance structures, controls and safeguards to meet CMMC 2.0 standards Depending on the results of your CMMC readiness assessment, you’ll likely need to make internal changes within your organization to meet new compliance requirements. Your advisor can help you determine specific changes and recommend strategies, processes or systems to implement. 4. Undergo regular assessments You’ll also likely need to undergo regular CMMC assessments in order to maintain compliance and remain eligible to bid on DoD contracts. However, these are self-assessments, as third-party assessment requirements are currently affected by the Phase II pause. Continue to engage with your advisor to make sure you’re prepared for your CMMC assessments so you don’t experience any unexpected surprises that limit your ability to bid on DoD contracts. What else should you know about CMMC readiness? Here’s what else businesses need to know to prepare for CMMC and meet cybersecurity readiness requirements: What is the latest DoD guidance on CMMC? The government’s guidance on CMMC continues to evolve, with the Phase II pause in July 2026 representing the latest significant shift in policy. Your advisor can help you stay on top of any new developments and adapt as needed. Does the commercial item exception apply to my products? Some organizations may benefit from an exception stating that providers of commercial items only need to achieve level one CMMC certification. An RPO can help you determine if this applies to you and help to build your organization’s commercial item representation. What processes or tools do you need to comply with CMMC? CMMC requirements change depending on which of the three levels your business falls under. Before you can determine which processes you need, you’ll first need to determine your level within the CMMC framework. How long does it take to become CMMC compliant? Depending on your CMMC level, achieving compliance will take anywhere from several months to well over a year. The specifics depend on your current cybersecurity readiness, the size and capabilities of your organization, your degree of advisory support and the particular requirements you aim to meet, with Level 3 compliance estimated to take as long as 18 months. Can businesses self-assess CMMC compliance? The Phase II pause means that self-assessment is currently the only option for businesses to demonstrate CMMC compliance. CMMC assessment rules originally required third-party assessments in certain circumstances, including a Level 2 third-party assessment by a C3PAO and a Level 3 third-party assessment by the Defense Contract Management Agency’s (DCMA) Defense Industrial Base Cybersecurity Assessment Center (DIBCAC). However, these requirements are currently paused and under review. Do organizations also need to be compliant with DFARS 252.204-7012 and 7019? The DoD assumes that organizations who are now starting to prepare for CMMC have already achieved compliance with DFARS 252.204-7012 and 7019. If your organization hasn’t done this yet, you’ll need to catch up to where the DoD expects you to be prior to starting your preparations for CMMC. How much does CMMC cost? The DoD has established a rough order of magnitude (ROM) of how much it is expected to cost organizations to achieve CMMC, broken down by size of business and shown as a percentage of annual income. You can find this assessment within the Federal Register Notice for Defense Federal Acquisition Regulation Supplement (DFARS) Case 2019-D041 . Note, this ROM assumes the organization is already compliant with DFARS 252.204-7012 and has all the required NIST SP 800-171 controls in place. Are CMMC costs allowable? The DoD understands that organizations will incur costs in preparing for and sustaining CMMC. Fortunately, the DoD has also determined that some of these costs are allowable indirect costs. An RPO can help you understand which costs are allowable and which are unallowable. Read more From compliance to confidence: Mastering the new CMMC requirements The 3 pillars of smarter cybersecurity program management The right cybersecurity framework boosts a business’s value
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Shadow AI: How to reduce the risks of unauthorized AI use
As AI continues to transform how many businesses operate, too few executives fully understand the risks that come alongside the rewards. One of the most prominent of those risks is called shadow AI. Most commonly appearing in organizations that don’t have a strong AI governance structure already in place, shadow AI can expose your business to financial, regulatory and reputational damage. But it’s also a risk you can dramatically reduce or even eliminate by putting thoughtful policies in place and properly training your team. Keep reading to learn more about what shadow AI is and how to protect against it. What is shadow AI? Shadow AI refers to the use of unapproved AI tools by employees within your business. This almost always happens because well-meaning team members are simply trying to do their jobs, but can create substantial business risks, like exposing your internal or customer data to public AI models. Shadow AI occurs when an organization doesn’t have strong AI governance or an AI use policy in place. Absent such oversight, team members often choose their own AI tools without considering whether those tools meet data privacy, regulatory, anti-bias or cybersecurity requirements. This far into the AI era, you should assume that many of your team members use AI as part of their daily workflows. That means if you don’t have clear AI policies to govern what tools your team uses or how you protect your data, you are already exposed to the risks of shadow AI. Why is shadow AI a business risk? Shadow AI is a significant business risk that can expose an unprepared organization to financial losses, reputational harm, regulatory action and cybersecurity threats. To understand how, consider the following scenario: Working to meet an urgent deadline, a manager at a financial services firm feeds a large dataset into an AI tool, asking the AI to analyze the data and draw conclusions that she can use in a presentation to her departmental leadership the next day. So far, seems reasonable, right? Analyzing large datasets is one of AI’s biggest strengths. But here’s the problem: The manager doesn’t realize that she’s picked a tool that uses its inputs for training data — which means it’s now absorbed all the proprietary customer data in the dataset she gave it. In this scenario, her company’s private customer details could start appearing in answers the AI tool gives to other users. Regulators will be furious, and so will any customers who find out what’s happened, which exposes the manager’s employer to fines, reputational damage and even litigation. If you want to take this example even further, imagine what could happen if the AI tool had security flaws that could allow hackers to reconstruct the full dataset. How does shadow AI happen? Shadow AI happens when an organization’s leadership fails to implement effective AI governance . If you want your employees to use AI in a way that protects your business and mitigates your risks, you need to show them how. Organizations that adopt AI piecemeal rather than through a cohesive enterprise strategy are typically most at risk for shadow AI. In these cases, shadow AI use typically builds up gradually, as team members turn to AI of their own initiative to solve problems or work faster. A few examples include: Putting internal data into a free chatbot model. Connecting an unauthorized AI assistant to company systems. Using an AI to make decisions that affect customers or team members. Asking a consumer-facing AI to summarize a video of a sensitive client meeting. Essentially, any scenario where someone on your team gives data to or relies on outputs from an AI that your IT and governance team hasn’t already approved can put your business at risk. What are the primary risks of shadow AI? Shadow AI use can create unexpected risks for your business. These can be financial, reputational or regulatory and can also include security risks. Financial costs: Shadow AI use can expose your business to fines, litigation and other costs associated with giving internal or customer data to unauthorized AI systems. Reputational damages: Customers, clients, partners or vendors whose data is exposed by shadow AI use won’t appreciate that — and neither will anyone else who hears about it. Regulatory challenges: AI use that violates regulatory or anti-bias requirements will generate ire from regulators, which can include sanctions, penalties, fines or corrective actions. Cybersecurity dangers: Security vulnerabilities within an unsanctioned AI tool could create cybersecurity risks by allowing hackers to gain access to your data or systems. Also consider that the quality of AI outputs depends heavily on the quality of the data being input . If your teams are using shadow AI tools outside of an organized, enterprise-level AI strategy, you likely don’t have an AI-ready data foundation (like a data lake house) either. This means that your shadow AI users, which may include executives, run the risk of making business decisions based on unapproved tools operating on poor-quality data. How to reduce shadow AI risks To reduce your shadow AI risks and cut down on unauthorized AI use, make AI a pillar of your overall enterprise risk management strategy . Here are key steps to effective AI risk management: Establish AI governance Setting up a formal AI governance structure establishes oversight on your team’s AI use and protects your business from shadow AI. Effective governance is an ongoing process that involves choosing a governance team, selecting approved AI tools, writing policies and seeking feedback from other stakeholders. Crucially, governance is also an opportunity to talk about how your business can use AI to work more efficiently and effectively. Approve enterprise AI tools Selecting and implementing specific AI tools for your team to use dramatically reduces your shadow AI risks. This is because enterprise-level AI options typically protect your data in a way that consumer AI products don’t. Create an AI policy An AI policy establishes written guidelines for how your team should use AI. Creating clear policies helps your team understand what’s allowed and what isn’t, which helps stop inadvertent shadow AI activities. Train employees You can’t expect your employees to follow your AI policies and responsibly mitigate AI-related risks without training. Like cybersecurity, this should be a process, not a one-time event, in order to keep your AI policies top of mind. Monitor AI use Your IT team and governance committee should monitor your organization’s AI use and continually assess your risk exposure. AI and AI-related risks are constantly evolving, and your policies and governance will need to, too. Read more AI ROI: How to get more business value from your AI spending AI governance checklist: A basic framework for your business AI implementation challenges: Why AI may fail to deliver ROI
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