By Tracy Holtz, Vice President, Cloud Solutions, Americas, TD SYNNEX
It hardly needs saying, but artificial intelligence (AI) in cloud networking has massive potential to revolutionize the way we all live and work.
From quickly defining and describing objects to natural language understanding (NLU) and answering commonly asked questions, AI is making leaps and bounds – streamlining processes that we couldn’t imagine abbreviating with machine intervention years (or even months) ago.
But like any valuable tool, it can be used for as much bad as it can be used for good.
For every AI researcher making new milestones with their innovations, there’s a hacker taking those advances and using them to nefarious ends: like voice cloning your loved ones to engage in virtual kidnapping, or tapping on large language models (LLMs) like WormGPT – aptly named “ChatGPT’s Malicious Cousin” – to create new types of malware and craft the perfect messages for their phishing schemes.
Now I don’t say all this to scare anyone. Rather, I mean it use it as a rallying call. AI is not a ‘nice to have’ anymore – as an industry, we need to understand it, secure the “good AI” to the best of our abilities and stay ahead of AI’s innovation curve if we don’t want it to be used against us.
So… How Do We Get Ready for Cloud-Enabled AI?
Getting ready for AI is a lot simpler than you’d expect – and it starts by establishing a targeted AI strategy at three key stages:
- Establish Zero Trust Foundations
Technical challenges are often the biggest hinderance in advancing cloud networking. Between new cloud adoption, technical debt and ensuring compatibility with legacy systems, adding AI capabilities to the mix can feel like throwing a wrench into a set of cogs you just got to start spinning.
While it may sound counterintuitive, successful AI adoptions are helping technicians solve many of these problems. This is mainly because successful AI adoptions involve building a system based on zero trust policies, and adopting industries have a willingness to make strategic updates to security and data strategies to match this shift.
A Few Signs That Show Your Cloud Network is Ready for AI:
- The cloud network can explicitly verify users on the network with identity and access management (IAM) tools.
- The cloud network includes endpoint security as well as endpoint management tools.
- The cloud network and its users follow least privilege policies when it comes to application and data management.
These foundational steps are the most important to make – because these tools and policies can help ensure users and networks are at least prepared to face an AI-enabled attack, even if their network is not going to have any AI capabilities to begin with.
- Get Ready for AI Implementation… With More Security!
The second step is all about comprehensively securing the AI tool itself and the entire network it lives in. Here’s why:
Just envision the profound impact of being able to type in a question like “What are the buying trends and revenue projections for my top 20 customer accounts?” and having a detailed report with all the answers in a matter of seconds. Now envision that kind of tool in the hands of someone who wants to extort money from your business – or even worse, destroy your business altogether.
This is why securing your AI tool is just as critical as building the right foundational environment for it.
Additional Data Strategies and Security Tools Needed for AI Adoption:
- Advanced Threat Protection, which helps ensure security is stretched across all endpoints that are connected to your cloud network.
- Privileged Identity Management enhances security capabilities to control service accounts, record privileged sessions, audit all access and more easily achieve compliance goals.
- Data Classification Policies help build a security-first culture and create a structured foundation for AI to work in.
- Sensitivity Labels also help AI discern the importance of specific data sets – ensuring users can access the appropriate documents and content for their needs.
These measures not only enhance security, but also lay the groundwork for AI to provide accurate and valuable insights.
- Spearhead AI Transformation
Once your foundations have been set and you’ve created an ideal network environment for AI, you’re ready to spearhead new transformation! I always recommend that partners take this transformational shift in three phases:
- The Technical Proof of Concept (POC) Phase - This is where an organization evaluates how the AI tool improves individual productivity, which typically involves deploying the new tool on a small scale in a controlled environment.
- Opportunity Identification Phase – Once you find out what your AI tool is best at, identify key business units that could use these skillsets to improve their day-to-day work. This phase also helps build familiarity with the tool, laying the groundwork for broader adoption.
- Transformational Efficiency Phase – The final phase is reserved for those who fully adopt AI into their business. In this phase, workflows are restructured and processes are re-aligned to unlock the full potential of AI usage in the organization.
The final piece of advice I have to give for AI-enabled cloud networking is this: AI adoption is much more than a technical shift. It is a cultural shift as well and requires participation from everyone in an organization – from the individual co-worker contributor all the way to the C-Suite – for it to be utilized to its fullest extent.
Let’s Get Ready for AI – Together!
If you’d like to learn more about AI in cloud networking and how you can begin implementing this tool in your managed service provider (MSP) business,our team at TD SYNNEX is here to help!
Recently, the TD SYNNEX team partnered with Microsoft 365 and its AI-enabled Copilot solution that can help you solve for each of these steps. To learn more about how you can build a stronger AI foundation with cutting-edge solutions, check out our Microsoft 365 Copilot solution guide and roadmap.
