Frequently Asked Questions

Shadow AI, Governance & Responsible Innovation

What is shadow AI and why do employees use it?

Shadow AI refers to the use of AI tools outside an organization’s approved systems or processes. Employees often turn to shadow AI to work faster or more efficiently when internal tools are too slow, limited, or lack necessary capabilities. This behavior typically signals gaps in internal systems, guidance, or available tools. Source

How can organizations drop shadow AI without stifling innovation?

Organizations can address shadow AI by setting clear boundaries, offering better tools, and providing practical training. Forward-thinking leaders define policies that promote safe experimentation and responsible AI use, while explaining the rationale behind the rules. Collaboration between data governance and learning teams helps build guardrails that guide innovation, not block it. Source

What role does training play in preventing shadow AI?

Training is essential for preventing shadow AI. Employees need to see real use cases, practice with actual tools, and understand the risks of using unauthorized systems. Data Society’s training programs are built inside existing workflows and focus on hands-on projects, helping employees gain both skill and confidence with approved AI tools. Source

Can responsible AI use be encouraged without fear tactics?

Yes. Empowering employees with information and alternatives, and framing policies as protective rather than punitive, builds trust and encourages compliance. Clear communication and practical training help foster a culture of responsible AI use. Source

How do you build trust in internal AI tools?

Trust is built through practical training and clear communication. When employees experience how approved AI tools save time, improve outcomes, and protect sensitive data, adoption happens naturally. Data Society’s training incorporates the tools organizations use, helping people build both skill and confidence. Source

What are signs that your current AI tools are not meeting employee needs?

Signs include increased use of external platforms, inconsistent workflows, and reliance on manual workarounds. These behaviors indicate a lack of usable, effective internal tools and highlight the need for better training and system improvements. Source

Features & Capabilities

What features and capabilities does Data Society offer?

Data Society provides hands-on, instructor-led upskilling programs, custom AI solutions, workforce development tools, industry-specific training, AI and data services (predictive models, R&D, cloud-native courses, project ideation, design thinking, machine learning, UI/UX analytics, rapid prototyping, executive technology coaching), and technology skills assessments. Integrations include Power BI, Tableau, ChatGPT, and Copilot for seamless workflows. Source

What are the key benefits of Data Society's products?

Key benefits include measurable ROI (e.g., 0,000 annual cost savings for HHS CoLab), operational efficiency, enhanced decision-making, equity and inclusivity in workforce development, seamless integration with existing systems, and proven results across industries. Source

What integrations does Data Society support?

Data Society supports integrations with Power BI (dynamic dashboards), Tableau (interactive analytics), ChatGPT (generative AI automation), and Copilot (process optimization). These integrations streamline data access, collaboration, and reduce manual work. Source

Pain Points & Solutions

What core problems does Data Society solve?

Data Society addresses misalignment between strategy and capability, siloed departments, low data and AI literacy, overreliance on technology without human enablement, weak governance, change fatigue, and lack of measurable outcomes. Solutions include tailored training, advisory services, and solution design focused on people, process, and technology. Source

What are the reasons behind the pain points Data Society solves?

Pain points stem from ambitious goals without workforce readiness, fragmented data ownership, lack of formal training, technology investments without human enablement, weak governance, cultural resistance, and unclear ROI. Data Society addresses these through tailored training, advisory, and solution design. Source

How does Data Society solve each pain point?

Data Society bridges strategy-capability gaps with tailored training, breaks down silos via integrations, boosts literacy with hands-on programs, enables human adoption through mentorship, strengthens governance with frameworks, manages change with communication, and delivers measurable ROI through KPIs and continuous tracking. Source

What KPIs and metrics are associated with the pain points Data Society solves?

KPIs include training completion rates, workforce competency percentages, data integration rates, collaboration indices, literacy assessment scores, tool adoption rates, governance policy adoption, compliance audit scores, change adoption rates, and ROI per initiative. Source

Use Cases & Case Studies

What industries does Data Society serve?

Data Society serves government, energy & utilities, media, healthcare, education, retail, financial services, aerospace & defense, professional services & consulting, and telecommunications. Source

Can you share examples of customer success stories and case studies?

Yes. Notable case studies include 0,000 annual cost savings for HHS CoLab (source), improved healthcare access for 125 million people via Optum Health (source), a 28% technical knowledge improvement for Discover Financial Services (source), and operational efficiency gains for the City of Dallas (source).

Who is the target audience for Data Society's products?

Target audiences include generators (professionals using data/AI daily), integrators (analysts and power users), creators (developers and data scientists), leaders (executives and strategists), and organizations in government, healthcare, financial services, aerospace & defense, consulting, media, retail, and energy sectors. Source

Support, Training & Implementation

What customer service and support does Data Society provide after purchase?

Data Society offers a Learning Hub and Virtual Teaching Assistant for real-time feedback, ongoing support and coaching, instructor-led training, and flexible delivery options (live online or in-person). These resources help with troubleshooting, maintenance, upgrades, and effective system use. Source

How does Data Society handle maintenance, upgrades, and troubleshooting?

Maintenance and upgrades are simplified through automated systems and the Learning Hub, which provides real-time feedback and accountability. Customers also benefit from ongoing mentorship, workshops, and office hours for troubleshooting and system optimization. Source

What training and technical support is available to help customers get started?

Data Society provides quick implementation, structured training programs, ongoing support, mentorship, interactive workshops, and flexible delivery (online or in-person). Cohorts are capped at 30 participants for personalized learning and active engagement. Source

How easy is it to implement Data Society's solutions?

Implementation is quick and efficient. Organizations can start with a focused project, equipping a small, cross-functional team with tools and support. The onboarding process is streamlined, with minimal resource strain due to automated systems and flexible training delivery. Source

Security & Compliance

What security and compliance certifications does Data Society have?

Data Society is ISO 9001:2015 certified, demonstrating its commitment to quality management and continuous improvement. This certification ensures solutions meet stringent standards for reliability and quality. Source

Competitive Differentiation

How does Data Society differ from similar products in the market?

Data Society stands out by offering tailored solutions for specific industry challenges, hands-on upskilling programs, equitable workforce development tools, seamless integrations, and a proven track record with over 50,000 learners including Fortune 500 and government organizations. Advantages vary by role: executives gain faster insights, managers benefit from automation, developers get advanced analytics support, and HR teams access tools for inclusivity. Source

Why should a customer choose Data Society?

Customers choose Data Society for its tailored solutions, live instructor-led training, equitable workforce development, proven track record, industry-specific benefits, and competitive advantages for different roles. Every role gains time to focus on higher-value work, making Data Society versatile for diverse organizational needs. Source

Shadow AI is often viewed as a compliance issue, but at its core, it is a leadership challenge. When employees use tools like ChatGPT or other generative AI systems without approval, they are typically responding to a gap.

Why It’s Time to Drop Shadow AI Without Dropping Innovation

Shadow AI is often viewed as a compliance issue, but at its core, it is a leadership challenge. When employees use tools like ChatGPT or other generative AI systems without approval, they are typically responding to a gap. That gap might stem from slow systems, unclear guidance, or missing capabilities. Instead of labeling this behavior as reckless, strong leaders treat it as feedback.

Shadow AI is not a fringe issue, it is a signal that internal systems are not meeting people’s needs. The real question is not whether it is happening, but how your organization will respond.

“You have to assume there is going to be usage out there,” says Merav Yuravlivker, Chief Learning Officer at Data Society Group. “Do your best to provide those conduits in a way that is compatible with your company’s mission and values.”

For CDOs and CLOs, this is a call to lead with transparency, foresight, and enablement.

MUST READ: From Compliance to Curiosity: How to Spark Intrinsic Motivation in Learners with Adult Learning Principles

Boundaries That Empower, Not Restrict

In many organizations, the instinct is to react to shadow AI with tight restrictions. But overly rigid AI policies can stifle innovation and slow down the very transformation AI is meant to accelerate. The most forward-thinking leaders strike a balance. They define boundaries that promote safe experimentation and responsible AI use, while clearly explaining the why behind the rules.

This approach doesn’t just protect the organization. It invites collaboration between data governance and learning teams to build guardrails that guide innovation, not block it.

“When people understand where the limits are, they tend to stick within them,” Yuravlivker explains. “It is a little bit of the carrot and a little bit of the stick.”

Better Tools Start with Better Training

Providing approved tools is an essential first step, but without training, it’s incomplete. One of the overlooked benefits of corporate training is reducing reliance on risky, unauthorized tools by empowering employees to use the right ones confidently. When organizations invest in artificial intelligence in corporate learning, training must go beyond theory, it needs to be practical, role-specific, and directly tied to day-to-day tasks.

For CLOs, this means moving past generic AI overviews and delivering training aligned to real business needs. For CDOs, it means partnering to build learning experiences around the AI tools and workflows teams are expected to adopt, closing the gap between policy and practice.

“That is why our training programs do not just teach skills,” Yuravlivker says. “We train people inside the systems they already use, and we build hands-on projects that let them see the real value.”

MUST READ: What Is Shadow AI? And Why It Matters More Than You Think

From Training to Trust: Building Sustainable Change

The true goal of corporate training isn’t just behavior change, it’s culture change. One of the key benefits of corporate training that incorporates artificial intelligence in corporate learning is building trust through real-world impact. When employees experience how internal AI tools help them save time, work smarter, and protect sensitive data, adoption happens naturally. With the right training, AI becomes less intimidating and more empowering. Trust forms not only in the technology itself, but also in leadership’s commitment to driving meaningful, innovation-ready learning environments.

“When we do prompt engineering courses or data and AI literacy courses, we incorporate the tools that the organization can use into the content,” says Yuravlivker. “That is a powerful way to help people build both skill and confidence.”

Your Role in Dropping Shadow AI

CLOs and CDOs are in a unique position to turn shadow AI into a growth opportunity. It is time to stop treating shadow AI as a rule-breaking problem and start treating it as a roadmap to smarter systems and stronger teams.

To truly drop shadow AI without dropping innovation, you need an integrated approach. This means responsible AI use that is backed by clear policies, supported by capable tools, and reinforced by meaningful training.

Data Society works with leaders like you to build trusted, usable learning programs that reduce shadow AI by design. Our training is built inside your workflows, focused on practical impact, and aligned with your governance standards.

If you’re ready to shift from reactive to responsible, we’re here to help.

Let’s explore how we can help your teams drop shadow AI and build a culture of secure, confident AI adoption.

Q&A: Drop Shadow AI

How can organizations drop shadow AI without stifling innovation?

 By setting clear boundaries, offering better tools, and training people on how to use them. Innovation thrives when employees understand the rules and feel supported.

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