Artificial intelligence (AI) is remarkable. It’s in a constant cycle of continuous improvement, transforming learning into technologies that manufacturers can leverage to gain efficiencies across all aspects of their businesses.
It may seem as though the use of AI is sudden in the industrial space and B2B companies are reaching an inflection point in 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 Industrial Internet of Things (IIoT), Big Data and similar tools to enhance your decision-making, productivity and supply chain management. For example, machine learning aids in training, automation and predictive equipment maintenance. All of these things center around gathering, analyzing and transforming data using algorithms powered by AI to drive actionable insights.
The speed of change associated with AI suggests manufacturers’ existing tools and those to come will need to 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 customers. The potential for mishandling of data 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. These policies set parameters, ensure ethical and responsible decision-making and add a layer of data protection that builds employee confidence and customer trust.
Two policies needed
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 large language models (LLMs) like ChatGPT, Claude, Gemini, etc.
- 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 prospect and customer data and proprietary information are used and protected under your company’s care. It includes specifics about how your company deploys AI technologies during 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 advancements are fluid. Your approach to your AI use policies should be much the same. A regular cadence of review and updates helps ensure your company keeps pace with AI innovation while also upholding the highest standards of accountability and ethics.
Set clear boundaries
Both internal and customer-facing policies serve to prevent unintended consequences that can arise from AI misuse, such as data breaches, violations of intellectual property or ethical lapses. These policies establish clear guidelines for data protection, ethical AI use and security measures to reduce risks like data leaks or mishandling of confidential information.
The policies also ensure accountability, defining stakeholders’ roles and responsibilities in protecting data and enforcing the use of AI technologies. As AI evolves, maintaining adaptable policies that are reviewed regularly will ensure your company stays ahead of the curve, balancing innovation with robust data protection practices.
By proactively implementing these policies, your company mitigates risks and positions itself as a leader in responsible AI adoption, building trust with employees and customers.
More than machine learning
Having an AI use policy doesn’t exempt you from assuming the calculated risk that comes with its myriad applications. 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 at scale. Predictive behavior analytics, historical data and other customer-centric information allow them to tailor messaging, recommendations and responses to individual customers across various channels.
Plugging data leaks
Using AI to support these centers of revenue generation and other operational areas broadens data access across a company. The ramifications of a data leak could understandably deter manufacturers from fully embracing AI — but avoidance of AI usage in itself could ironically 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 are a tactical step you can take, but threats as serious as data leaks point to the importance of having internal and customer-facing AI use policies in place to drive the larger protection strategy.
Explain the ‘why’
Ultimately, an intentional and 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 buy-in of internal and external stakeholders, the policy is little more than a document.
Be clear and transparent in explaining the purpose of your policy to employees and customers. Help them understand the “why” by speaking plainly about the 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, yet progressive, partner. For employees, the policy marks a clear path forward as more workplace AI technologies are implemented. It also provides 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.
Greg Linnemanstons is the president of Weidert Group, a full-service HubSpot partner agency that helps industrials and the businesses that serve them grow through integrated marketing and sales strategies. He previously spent more than 18 years in senior marketing and sales roles at Fortune 500 companies.
