Executive Summary:
Artificial intelligence (AI) solutions are increasing in popularity – largely because they automate systems and increase workforce efficiency – and Intelisys Sales Partners can capitalize on the surging demand. The AI solutions in the Intelisys catalog can be divided into 4 main categories: customer experience AI, generative AI, custom AI development, and AI products. When pursuing an AI deal, Sales Partners should start the AI conversation with an understanding of industry-specific use cases, and then ask questions related to the organization’s pain points, data readiness, and business objectives. They should also suggest that organizations conduct an AI readiness assessment before holding an AI workshop and building a proof of concept. For more information, Sales Partners can access additional resources from Intelisys – including blog posts, SE webinars, and on-demand courses on AI solutions.
According to recent government surveys, as many as 40% of employees are already using AI for work. And why are companies turning to AI? There are 2 main drivers:
- Systems automation. AI solutions can reduce the reliance on human inputs for key processes.
- Workforce efficiency. AI solutions can help workers complete tasks faster.
The integration of systems automation and workforce efficiency enhances a company’s competitiveness. And in the world of ever-expanding AI capabilities, nobody wants to be left behind.
From custom AI solutions to off-the-shelf products, AI solutions are in demand. For Intelisys Sales Partners, that means one thing: It’s time to master the art of selling them. In this comprehensive AI solutions guide, we’ll break down the 4 main categories of AI solutions in the Intelisys catalog – and share some ideas for starting the AI conversation with clients.
4 AI Categories Sales Partners Should Understand
While most organizations could benefit from the efficiency that AI provides, their specific needs and expectations will vary. Your responsibility is to align clients with the solutions that address their challenges and achieve their business objectives. To do that, you’ll need a general understanding of the types of AI solutions that are available.
AI Solutions can be broken down into 4 main categories:
- Customer Experience AI
- Generative AI
- Custom AI Development
- AI Products
Below, we’ll analyze these categories and share common use cases for each.
Customer Experience AI
In a recent survey, 67% of Sales Partners said that, in 2024, they saw the greatest growth in one particular area: Customer Experience (CX). This growth is largely due to AI. CX solutions are leveraging AI like never before, and the enhanced capacity that AI provides has quickly increased demand.
Companies are learning that, thanks to AI, CX solutions can now automate and optimize customer interactions, which often enhances the customer experience. That, in turn, increases sales – while reducing the reliance on the performance of human agents.
Here are some specific AI use cases in the CX space:
- AI chatbots
- AI detection of customer sentiment (with AI-generated summaries)
- Precise outbound messaging
- Optimized training for agents
When identifying potential CX opportunities, look for companies that are especially likely to invest heavily in CX solutions. These tend to be businesses that see CX as strategically vital and have complex service requirements.
Some companies might hesitate to swap out their current CX infrastructure for newer models that incorporate AI. If you encounter this roadblock, remind key stakeholders that AI brings major efficiency gains – and stress your willingness to identify the exact CX solution that will meet their business objectives.
In other cases, swapping out a CCaaS platform might not be the best option for a business because of existing contract terms or the potential for business disruption. Fortunately for businesses in this situation, there are many standalone AI solutions with contact center integrations that enhance the agent/customer experience.
For more CX insights, read our recent post on spotting the largest CX opportunities.
Generative AI
The term “generative AI” refers to AI technology that can create new content – including text, audio, images, and video. This category includes “large language models” (LLMs) like ChatGPT.
For much of the world, the emergence of ChatGPT signaled AI’s arrival as a mainstream force in modern life. And while generative AI is far from the only influential AI on the market, it does represent a major AI category. It’s something many of your clients are likely already using – and you can help them leverage it even further.
There’s been an explosion of both private and open-source LLMs. Companies are using LLMs for:
- Content creation
- Customer support
- Language translation
- Data analysis
- Coding assistance
- Education and training
With each of the use cases, AI can increase efficiency while simultaneously improving results.
Generative AI is a dynamic field, with new models emerging constantly. The latest iterations of generative AI offer improved user interactions and enhanced capabilities – which will increase demand even further.
Custom AI Development
While LLMs like ChatGPT can provide value to a company, organizations often want something more: a custom AI tool that corresponds to their specific needs. Luckily, platforms are now offering exactly that.
Many companies are turning to “low-code” or “no-code” platforms to simplify AI development. These platforms allow users without extensive coding knowledge to train LLMs on their own datasets. Microsoft Copilot Studio is an excellent example, helping users create a personalized “agent.”
Oftentimes, custom AI development occurs on a public cloud platform like Azure or AWS. These deals tend to offer minimal margins for Sales Partners, with Microsoft Copilot providing margins in the range of just 3-5% – but they can still be lucrative if you layer on additional managed services.
Sales Partners can also cash in on custom AI development through solutions built on private cloud platforms. Private clouds offer a secure computing platform for customers in healthcare and finance with compliance standards such as HIPAA, PCI-DSS, FINRA, GLBA, NYDFS, etc.
When identifying custom AI development opportunities, it’s often best to start small. Help your customers identify a clear problem or inefficiency as an initial AI use case – preferably something that offers a quick return on investment. From there, you can build more complex use cases to gain customer confidence.
AI Products
In addition to creating custom solutions or using existing generative AI tools, many businesses may be interested in buying “off-the-shelf” AI products. These solutions are designed for easy integration, which makes them appealing to stakeholders – especially those who remain wary of incorporating AI into their business operations on a larger scale.
Examples of AI products include:
- Project management and scheduling tools
- Transcription tools and meeting assistants
- Managed detection and response (MDR) for cybersecurity
- Email tools
- Image and text generators
These types of products often represent a “quick win” for Sales Partners. Will you earn an ongoing commission, as you would for an MSP or a complex solution with ongoing integration needs? No – but you can still capitalize on the AI revolution, then continue discussing additional AI solutions with the client down the road.
Starting the AI Conversation
The first step towards any AI deal is initiating a dialogue. And how can you start the AI conversation? First of all, you need to know the specific AI use cases that are most prevalent in a company’s industry. Then, you have to ask the right questions while sticking to a strategy that prioritizes the easiest entry points.
Industry-Specific AI Use Cases
One of the main reasons AI is becoming so popular is that it offers tangible benefits across industries. Whether a company is saving lives, selling gadgets, or shipping boxes around the world, artificial intelligence will help it automate systems and increase efficiency.
Here are some specific use cases for AI in 3 key industries.
Healthcare
- Enhanced patient care. AI systems can improve the speed and accuracy of diagnoses – leading to improved patient outcomes.
- Efficient operations. By tracking inventory and automating staff management, AI solutions eliminate waste and optimize workflows.
- Data security. Few organizations possess as much sensitive data as a hospital – and AI solutions help keep that data secure.
Retail
- Customer behavior analysis. AI solutions can summarize key data points – including foot traffic and purchasing patterns – to help companies make smarter decisions around prices and inventory.
- Personalized experiences. Through chatbots and automated recommendations, AI can improve the customer experience – which ultimately boosts sales and brand loyalty.
- Fraud prevention. AI solutions can detect fraud and limit costly shrinkage.
Transportation & Logistics
- Optimized fleet operations. AI solutions boost fleet efficiency by monitoring driver behavior, predicting maintenance needs, and identifying optimal routes.
- Reduced downtime. From breakdowns to delays, AI can catch potential disruptions before they derail operations.
- Automated warehouse management. With AI solutions, organizations can mitigate the risk of human error in inventory tracking, packing, and fulfillment.
Three Key Questions for Every Customer
Regardless of a client’s industry, you’ll want to base the AI conversation around 3 main questions:
- What are your current pain points?
- Are you confident your data is ready to be incorporated into an AI solution? (Remind stakeholders that the quality and security of an organization’s data usually determines the AI solution’s effectiveness. You might also want to ask, “Do you have a data management lifecycle policy?”)
- What metrics would indicate success?
These questions will help you guide the organization toward the AI solutions that best meet their objectives.
It’s also worth noting that AI conversations might start with a discussion of technology – but the focus often shifts towards ROI. Companies want to know the tangible effects that AI solutions will have on their bottom line.
Common Entry Points
The ideal entry point for the AI conversation will depend on the prospect. That said, there are 3 general strategies you should always keep in mind:
- The “start small” principle. For many end-users, AI technology still feels new. Some stakeholders might be hesitant to incorporate AI at the heart of their business operations. This is where those “off-the-shelf” AI products come in handy.
- The trust-building approach. By meeting clients where they’re at in their AI journey, you can establish yourself as a reliable partner – making it more likely they’ll eventually enlist you to guide them towards more comprehensive AI solutions.
- Expansion pathways. Try to predict which additional AI solutions a client might want to adopt in the future. This helps you identify upselling and cross-selling opportunities.
Next Steps for Sales Partners
Are you ready to increase your revenues from AI solutions? Then it’s time to act on the information we’ve provided in this comprehensive guide.
Getting Started
Once you’ve initiated the AI conversation with a prospect, consider taking these 3 steps:
- Step 1: Suggest an AI readiness assessment. This assessment will evaluate the organization’s data and compute infrastructure to see if it’s ready for an AI solution.
- Step 2: Encourage the organization to hold an AI workshop. At the workshop, key stakeholders can evaluate use cases, explore potential processes, and define the outcomes they hope to achieve. This step promotes buy-in across the organization.
- Step 3: Build a proof of concept. Given the AI talent shortage at most organizations, this step is often best outsourced to third-party experts.
For more information on implementation, read here: How End-Users Can Implement AI Correctly (and Win the AI Revolution).
Learning More
Eager for more insights on AI solutions? You should be! The more you know about AI, the better you’ll be positioned to capitalize on the technologies of today – and tomorrow.
Start by enrolling in our AI course series – designed to make you a genuine expert in the field. And check out additional resources from Intelisys– including this blog post on implementing AI solutions and this SE Webinar on monetizing AI (available through Intelisys University).
Also, don’t forget to reach out to our Solutions Engineers (SEs) for additional support.
