AI in Business: Balancing Productivity with Data Security

Reported by : Maizatul Ilma 

Artificial intelligence has quickly become a core component of today’s workplace. Employees now rely on AI tools to draft emails, summarize documents, analyze data, and complete tasks more efficiently. As a result, AI is increasingly driving productivity and enhancing how businesses operate.

According to Gallup’s 2024 workplace AI adoption report by Ryan Pendell, the number of employees using AI at work has nearly doubled in the past two years. Another study found that professionals given access to ChatGPT were 37% more productive on writing tasks. These insights highlight how rapidly organizations are integrating AI to support efficiency and innovation.

However, the rapid rise of AI usage also brings new challenges. Gallup researcher Christos Makridis reported that although 93% of organizations have begun using AI, only 15% of U.S. employees say their employer has provided a clear plan for integrating AI into their work. Without proper guidance and training, employees may unintentionally expose sensitive information or rely too heavily on AI‑generated outputs. This can undermine data security and lead to poor decision‑making.
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AI can significantly improve efficiency, but organizations must also establish clear ways of working around these technologies. Without thoughtful processes, governance, and responsible practices, the benefits of AI can quickly introduce new risks to productivity and data security.

​The Growing Role of AI in Business Productivity

​As organizations continue adopting digital technologies, artificial intelligence has become a valuable tool for supporting everyday work. By assisting with routine tasks and helping teams analyze information more efficiently, AI enables employees to focus on strategic thinking, problem‑solving, and decision‑making. The following examples illustrate how AI is enhancing productivity across different business functions.

1. Faster Information Processing

• AI can quickly review and organize large amounts of information, helping employees find key insights without spending too much time searching through data.
• Example: A finance team might use AI to scan hundreds of expense records to identify unusual transactions that need further review.

2. Efficient Research Support

• AI tools help employees gather information faster and explore topics more efficiently when preparing reports or projects.
• Example: Business analyst may use AI to summarize several industry articles before compiling the final analysis.

3. Idea Development

• AI assists employees generate new ideas by offering different perspectives or suggesting additional points during brainstorming or planning sessions.
• Example: A marketing team uses AI to create fresh concepts for campaign themes or messaging strategies.

4. Data-Driven Insights

• AI can analyze data and highlight important patterns, enabling employees to understand information more easily and make informed decisions.
• Example: Marketing teams may use AI to understand customer behavior by analyzing data collected from real customers, including surveys, purchase histories, and feedback records.

5. Problem-Solving Support

• Employees can use AI to explore possible solutions when they encounter challenges in their work, helping them resolve issues more efficiently.
• Example: A software developer asks an AI assistant for suggestions when debugging code.

6. Reducing Administrative Work

• AI supports routine administrative tasks such as drafting emails, organizing documents, and summarizing meetings, allowing employees to focus on higher-value work.
• Example: A manager uses AI to generate a summary and action-item list after a long project meeting.

​Why Employees Should Not Rely Too Heavily on AI

While AI can significantly improve workplace productivity, it should function as a support tool rather than a replacement for human judgment. Organizations that rely too heavily on AI without proper oversight may introduce new operational and data risks.
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IBM reports that 13% of organizations have faced AI‑related security breaches, with most incidents leading to data compromise or operational disruption.

While AI can improve efficiency, relying on it too heavily may cause employees to overlook errors, miss important context, or make poor decisions. AI should support, not replace, human judgment and critical thinking. The following points explain why organizations should avoid overdependence on AI in everyday work.

1. AI May Produce Inaccurate Information

• AI systems can generate incorrect or incomplete responses, so employees must carefully review and verify the information before using it.
• Example: If an employee uses AI to summarize a long report, the output may miss important details or inaccurately represent the content.

2. Limited Understanding of Business Context

• AI does not fully understand internal company procedures, priorities, or operating environments, which may lead to suggestions that do not align with business goals.
• Example: AI may produce a marketing strategy that seems helpful but fails to consider the company’s budget, policies, or specific objectives.

3. Reduced Critical Thinking

• Employees who depend too heavily on AI may stop analyzing information independently, limiting opportunities to develop critical thinking and problem‑solving skills.
• Example: A web developer who frequently uses AI to generate code may gradually lose the chance to improve their own coding abilities.

4. Lack of Human Judgment

• AI cannot replace human experience, intuition, or professional judgment, especially in situations involving complex decisions or long‑term consequences.
• Example: HR professionals cannot rely solely on AI to choose candidates, they still need to review each applicant’s background and qualifications.

​Understanding the Data Risks Behind AI Tools

AI can also create data security risks when employees misuse these tools. Many employees unknowingly share sensitive information with generative AI platforms, and around 71.6% of AI access occurs through non‑corporate accounts, increasing the chance of data leakage (Underhill, 2025). Because many AI tools require users to input information, confidential data may be exposed if employees are unaware of the risks. Understanding these issues is crucial to ensure AI is used responsibly within the organization.

1. Data Privacy Risks

• Employees may unintentionally expose confidential company or customer information when entering sensitive details into AI tools.
• Example: An employee may include internal notes, system access details, or customer data while asking AI for help, which can compromise privacy.

2. Loss of Control Over Shared Data

• Once information is entered into external AI tools, organizations may have limited control over how the data is stored, processed, or retained.
• Example: If an employee pastes a confidential company report into an AI tool, the information may be stored outside the company’s secure systems.

3. Lack of Employee Awareness

• Many employees do not understand how AI tools process or store information, which increases the risk of accidentally sharing sensitive data.
• Example: A customer support employee may copy a customer’s personal details into an AI tool to draft a response, unintentionally exposing sensitive information.

4. Unauthorized Use of AI Tools

• Employees may use AI tools that are not approved by the organization, increasing the risk of exposing confidential business data.
• Example: A company may require employees to use Microsoft Copilot, but some may still use unapproved tools like ChatGPT and enter sensitive company information.

​Preparing Employees to Use AI Safely and Responsibly

As AI becomes more widely used in the workplace, organizations must ensure employees understand how to use these tools responsibly. While AI can support productivity and innovation, its benefits can only be fully realized when employees are aware of both its capabilities and limitations.

1. Establish Clear AI Usage Guidelines

• Organizations should define how AI tools should be used and specify what types of information must not be shared with them.
• Example: A company may implement a policy that prohibits employees from entering internal reports, customer data, or private information into public AI tools.

2. Review and Verify

• Employees should remain responsible for reviewing AI‑generated information and ensuring its accuracy before using or sharing it.
• Example: When AI produces a meeting summary, employees should check the content to ensure key details are accurate before distributing it.

3. Define Sensitive Information

• Organizations must clearly explain which types of data are confidential and should not be shared with external platforms.
• Example: Sensitive information may include internal documents, customer records, financial reports, and system access credentials.

4. Use Approved AI Tools

• Companies should require employees to use AI tools that meet organizational security and data protection standards.
• Example: If employees use unapproved tools, they must avoid entering any confidential or sensitive company information.

5. Provide Employee Training

• Proper AI training helps employees understand AI capabilities, risks, and best practices for safe and responsible usage.
• Example: A company may conduct workshops led by AI experts to teach employees about AI risks, data protection, and responsible usage.

Conclusion

As AI continues to shape the modern workplace, organizations must do more than simply adopt new tools. The real challenge lies in how work is managed, how decisions are made, and how information is handled responsibly. Productivity gains from AI are only sustainable when supported by clear processes, thoughtful governance, and a culture of accountability.

At 57Network, we focus on helping organizations build effective Modern Work Management practices. By designing structured workflows, improving collaboration, and establishing responsible ways of working, we help teams navigate technological change while maintaining clarity, security, and operational discipline.

Technology will continue to evolve, but organizations that succeed will be those that combine innovation with clear systems, responsible practices, and empowered teams. With the right work management approach, businesses can embrace tools like AI while maintaining control, protecting sensitive information, and enabling their people to perform at their best.

💡 Want to build a more secure and efficient workplace? Connect with us today!

References:
AI Use at Work Has Nearly Doubled in Two Years

​Play the Long Game With Human-AI Collaboration

IBM Report: 13% Of Organizations Reported Breaches Of AI Models Or Applications, 97% Of Which Reported Lacking Proper AI Access Controls

77% of Employees Share Company Secrets on ChatGPT, Report Warns