While large-scale enterprises have a clear advantage—namely, more resources and more headcount—when it comes to implementing AI, they also face unique challenges compared to smaller, more nimble companies.
So, how can enterprises pivot efficiently, align their teams, and successfully execute an AI transformation?
With a large number of enterprise-size customers, our team at RingCentral has been advising and supporting large-scale AI implementation projects—here are some best practices for companies looking to adopt AI tools.
6 best practices for implementing AI in an enterprise
While every enterprise’s implementation plan is unique, there are a few essential steps that almost all companies, regardless of industry or size, should consider once they’ve selected an AI solution:
1. Define your business goals and use cases
In short, why are you implementing AI?
This is a step that should’ve been completed when you were selecting your AI solution, but in reality, it’s a process that continues through the implementation stage because you’ll need to set up reporting and dashboards to track performance against those goals.
So, once you’ve identified your business goals—whether that’s addressing inefficiencies in your contact center, or reducing ramp-up time for new hires—make sure you have basic reporting set up as one of your first priorities.
This will set your team up for success and empower them to evaluate AI’s impact and communicate key metrics (around cost savings, improved customer satisfaction, and so on) clearly to stakeholders and the leadership team later.
2. Consider your budget and resources
Your implementation process will also vary depending on your budget and resources. If you have the budget to dedicate to a white-glove onboarding service, that is ideal because it takes the burden off your own IT team or other internal teams. Not only that, paying for this service may also end up saving you money because it reduces the costs of employee training or downtime while implementing the AI tool.
For example, RingCentral’s Professional Services program comes with experts who advise on:
- pre-deployment strategic planning,
- time, resource, and cost estimations,
- optimization recommendations,
- and more
3. Have a change management plan
As part of your implementation process, you should have a robust change management plan in place that can preemptively address employee concerns, provide fallback options in case something goes wrong during implementation, and so on.
If you’re using your vendor’s onboarding service, they will be able to support you with this step.
4. Provide ongoing training
Like any other software, training your team on how to use a new AI tool isn’t a one-off project. Most AI tools are continuously adding new features as the technology evolves, and your teams will benefit from ongoing education and training. This will increase not only adoption, but also your return on investment and ensure that everyone on the team is getting the most out of your new tools.
5. Integrate your tech stack
One of the most important steps in any implementation project is ensuring you have integrations with all your core systems set up properly. Depending on who is using the AI tool, you may need to take a cross-departmental approach and collaborate with other departments to cover all your internal tools.
RingCentral, for example, not only has AI features but also integrates with other AI solutions such as Chorus.ai, Gong, Theta Lake, Talkwalker, and more to connect and sync all your data sources.
6. Secure your system
Finally, make sure you have the appropriate security and data privacy features set up in your new AI tool. Almost 75% of IT security professionals report that their organizations are suffering significant impact from AI-powered threats, and with AI-driven voice and video fraud continuing to proliferate, it’s crucial for enterprise organizations to prioritize the security of their (and their customers’) data when adopting new tools.
RingCentral, for example, lays out details about how its AI products use data, for which purposes and for which output, in Product Privacy Datasheets that are available for each of its services. (Learn more about RingCentral’s approach to AI privacy.)
Looking to implement AI in your enterprise?
Beyond following the best practices above, the best way to successfully implement a new AI tool is by choosing one that is well-designed, intuitive, and secure.
Not only will this increase adoption by employees, it also ensures your organization is compliant, protected, and set up for success from the start.
Book a demo with our team to learn more about RingCentral’s AI solutions and the implementation process for large enterprises!
Originally published Dec 17, 2024
