Preparing to Deploy AI in the Enterprise: Five Things to Know

Anurag Lal Anurag Lal, President and CEO of Infinite Convergence.

AI brings an unprecedented opportunity for enterprises to increase productivity and efficiency, improve decision making, personalize customer service, optimize communication and collaboration, and much more.

Enterprises today are understandably eager to leverage the transformative potential of this technology. Research released earlier this year by IBM revealed that about 40% of IT professionals surveyed reported that their organizations are currently exploring or experimenting with AI.

Even as organizations rush to experiment, deploy, and use AI, many feel unprepared to do so. An AI Readiness Index survey by Cisco found that 86% of companies across the globe are not fully prepared to leverage AI and AI-powered technologies to the fullest potential.

To better prepare for the deployment of AI technologies and more successfully unlock AI’s transformative potential, enterprises should keep the following five things in mind:

1. Pilot projects are a great way to test the AI waters

Starting small with pilot projects is a great way for enterprises to experiment with AI. Testing the AI waters in this way can help organizations and employees build familiarity with the technology and become more comfortable using it. These projects can also help identify potential issues as well as surface valuable insights and feedback from employees as they work with the technology.

AI pilot projects with clear and measurable objectives allow enterprises to capture learnings and best practices that can help inform strategies for deploying AI on a larger scale in the enterprise.

2. AI guardrails are critical for data protection and privacy

According to a poll of global digital trust professionals by the Information Systems Audit and Control Association (ISACA), only 10% of those surveyed said a formal comprehensive AI policy is in place, and more than one in four say no policy exists and there is no plan for one.

Successful adoption of AI requires enterprises to develop policies and protocols for the appropriate and responsible use of the technology.

Establishing guardrails around AI usage is critical to preventing data breaches, avoiding compliance violations and preventing misuse of protected information. AI usage policies should clearly define which AI tools are verified and approved for use, what data can be used in AI queries and what data should not be used, what type of tasks AI can perform, and how AI outputs should be evaluated and vetted for accuracy.

3. Employee training promotes the safe and responsible use of AI

For AI technologies to deliver the most value to organizations, employees need training on the safe and responsible use of these technologies.

Many enterprises are lagging when it comes to providing employee training on how to use AI securely and effectively. The ISACA poll found that despite employees quickly moving forward with the use of the technology, only 6% of organizations responding to the survey said they provide training to all staff on AI, and more than half (54%) said that no AI training at all is provided, even to teams directly impacted by AI.

Before deploying AI, it is important to train employees on best practices for responsibly using AI and educate them on the damaging consequences of misusing the technology including compromised data security and privacy.

AI training should also include a review of the organization’s AI usage policies with an emphasis on what data can be included in AI queries and what is not permitted. Employees should also be cautioned not to automatically trust content generated by AI and be advised that humans should review and edit all outputs created by AI tools.

With AI continuing to transform how work gets done, regular employee training focusing on the latest AI developments and best practices is critical to minimizing the risk of human error.

4. Keeping up with evolving regulations is a must to ensure compliance

As rapid adoption of AI continues to transform enterprises in every industry and sector, policymakers are scrambling to regulate the use of this technology. This evolving regulatory landscape requires organizations to stay abreast of regulatory changes to ensure that AI-powered systems and services remain compliant.

In the U.S. this year, at least 45 states, Puerto Rico, the Virgin Islands and Washington, D.C., introduced AI bills, and 31 states, Puerto Rico and the Virgin Islands adopted resolutions or enacted AI legislation, according to the National Conference of State Legislatures.

Outside the U.S., the European Union (EU) enacted the world’s first comprehensive artificial intelligence (AI) regulation. According to the EU, “the aim of the new rules is to foster trustworthy AI in Europe and beyond, by ensuring that AI systems respect fundamental rights, safety, and ethical principles and by addressing risks of very powerful and impactful AI models”.

Before rolling out the use of AI technology, enterprises should understand compliance regulations affecting their industry and closely monitor evolving regulations. Enterprises should also understand that the stakes are high when it comes to regulatory compliance. Failing to comply with regulations could result in fines, penalties, reputational damage, and loss of consumer trust.

5. AI solutions designed for the enterprise are the safest and most secure way to deploy AI

Whether it is a mobile messaging platform with integrated AI features or any other type of AI tool, enterprises should not only be looking at AI applications in relation to their business benefits but should also closely examine the security and data practices of these applications. Before selecting any AI tool, IT decision makers should vet these tools to ensure security and privacy practices meet or exceed the standards of their organization. AI tools that don’t meet enterprise standards can expose organizations to cyber threats and data breaches. According to a recent study from HiddenLayer, 77% of companies have already faced AI breaches.

Not every AI tool is built for enterprise use. Before deploying any AI solution, enterprises need to ensure the solution is enterprise-grade - meaning architected with E2EE (end-to-end encryption) and private by default. Enterprises should also have a clear understanding how AI solutions process, store, and use data.

When it comes to AI-powered mobile messaging platforms, enterprises should prioritize the selection of a platform that is secure, compliant and under their control. That describes NetSfere’s Net-C. Net-C is designed to provide a secure AI experience unique to each organization without integrating with any open source chat/AI functionalities and without any data or information ever leaving the enterprise.

Wrapping up

While many enterprises are rushing to deploy AI, to unlock the full potential of the technology requires a little less speed and a little more preparation.

In the words of Benjamin Franklin: “By failing to prepare, you are preparing to fail”.

This old adage is true of many things in life and business including AI deployments.

Enterprises that prepare for AI rollouts by developing pilot programs, establishing AI policies, providing employees with AI training, keeping up with evolving regulations, and selecting AI tools built for the enterprises are best positioned to unlock the full value of AI technology safely and securely.



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