AI Use Policies: A Strategic Necessity for Manufacturers

Artificial intelligence (AI) is remarkable. It’s always in a cycle of continuous improvement, transforming learning into technologies that manufacturers can leverage to gain efficiencies.

It may seem as though the use of AI is sudden in the industrial space and B2B companies are reaching an inflection point in terms of adopting AI technologies. The truth is that many aspects of AI are already well-established in manufacturing environments. 

Industry 4.0 is driven by intelligent digital technologies. Chances are, you’ve integrated the Internet of Things (IoT), Big Data, and similar tools to enhance your decision-making, productivity, flexibility, and supply chain management. Machine learning aids in training, automation, and predictive equipment maintenance. All of these things center around gathering, analyzing, and transforming data into actionable algorithms powered by AI.

The pace of change associated with AI suggests manufacturers’ existing AI tools and those to come will collect greater amounts of data, including highly confidential information. Operationally, this likely means more people in more departments will access sensitive data related to your company or your customers. The potential for data mishandling increases exponentially, as does the risk of exposing your company to legal, financial, and reputational jeopardy.

Establishing internal and customer-facing AI Use Policies is a best practice whose time has come in manufacturing. These policies set parameters, ensure ethical and responsible decision-making, and add a layer of data protection that builds employee confidence and customer trust.

The Necessity of Having Two Policies

The fundamental difference between internal and customer-facing AI Use Policies is intent.

Internal Policies

An internal policy guides employee conduct when using AI technologies, and typically includes items such as: 

• Permitted and non-permitted uses of AI in assisting with day-to-day work
• Prohibited practices related to inputting sensitive information into AI large language models (LLMs)
• Training and/or clearance requirements to access and use AI technologies
• Consequences of policy violation (reprimand, termination, etc.) 

Customer-facing Policies

A customer-facing policy sets expectations about how data and proprietary information is used and protected under your company’s care. It includes specifics about how your company deploys AI technologies during the course of  normal interactions with customers, partners, and the public. 

This policy may include:

• Privacy policy and confidentiality  disclosures
• Refusal and limitations of AI use that infringes upon copyrights, intellectual property, or other legal protections
• Data quality and sharing requirements

These guidelines may suggest that once an AI Use Policy is written, it’s rigid and permanent. In fact, the opposite is true.

The past few years have demonstrated that AI is fluid by nature — rapidly changing and adapting to the technologies of the moment. Your approach to your AI Use Policies should be much the same. A regular cadence of review and updates provides the twofold benefit of ensuring your company keeps pace with AI innovation while also upholding the highest standards of accountability and ethics.

More Than Machine Learning

Having an AI Use Policy doesn’t automatically exempt you from assuming the calculated risk that comes with the proliferation of AI in B2B industries. Vigilance is key, and it begins with understanding where and how AI technologies are relied upon throughout your operation.

In addition to machine learning, AI technologies help your marketing, sales, and customer service teams personalize customer experiences. Predictive behavior analytics, historical data, and other customer-centric information allows them to tailor messaging, recommendations, and responses to individual customers across various channels.

Plugging Data Leaks

Using AI to support these revenue centers and other operational areas means more people access data. It substantially increases the potential for data breaches — a perennial concern for both manufacturers and customers. The ramifications of a data leak can understandably deter manufacturers from fully leveraging AI, which can erode competitive advantage and amplify business risk. 

Implementing security measures with software such as Nightfall AI and LLMShield to prevent uploads of sensitive information to LLMs is a partial solution. But, it’s one tactical step. Threats as serious as data leaks point to the importance of having internal and customer-facing AI Use Policies in place to drive the organization’s overall protection strategy.

Policies Against Unintended Consequences

An AI Use Policy establishes clear boundaries around your company’s responsible and ethical use of AI technologies.

Policy verbiage reflects your company’s specific values and principles, and typically covers these common topics:

1. Transparency and trust: Explains how decisions and processes related to AI technologies are made and enforced, data disclosure, and storage.
2. Ethics and integrity: Delineates principles that guide how AI technologies will and will not be used in accordance with corporate and personal core values.
3. Accountability: Defines the stakeholders, their roles, and individual responsibilities in protecting data and enforcing AI Use Policies.
4. Security: Mitigates cybersecurity risks and ensures AI technologies are consistently reliable and secure.
5. Adaptability: Establishes how continuous learning and policies will evolve to accommodate the progression and possible challenges of AI technologies.
6. Legal compliance: Aligns AI practices, use, and functions with governing regulatory authorities.

Explain The “Why”

Ultimately, an intentional, well-crafted AI Use Policy empowers manufacturers to harness the full potential of AI technologies while maintaining trust, transparency, and security. However, without the full support of internal and external stakeholders, the policy is little more than a document.

Be clear and transparent in explaining the purpose of the AI Use Policy to your employees and customers. Help them understand the “why” behind the policy by speaking plainly about your company’s commitment to responsible and ethical AI use.

For customers, the policy signals a promise to uphold high standards and assurance that their proprietary information is in the hands of a trusted partner. For employees, the policy clearly marks their path forward as more workplace AI technologies are implemented. It also presents them with protections and opportunities to serve customers and each other with greater care and efficiency.

The reach and progression of AI is redefining the industrial space and manufacturers’ place in it. Define your company as a leader in responsible AI adoption by proactively establishing internal and customer-facing AI Use Policies that guide and protect your customers, employees, and company.

Before you dig into creating your AI Use Policy, it’s a good idea to get up to speed on what’s happening in the ever-changing world of AI. We’ve got a pulse on the latest info and compiled it in the Weidert Group Artificial Intelligence Resource Library. Visit any time for blog articles, videos, and insights from our team.

This article originally appeared in Insight On Manufacturing, November 2024.