Cheatsheet for Screening AI Vendors: The Only Checklist You Need

Every AI solution claims to be a “game changer”. With so much noise, it’s easy to get swayed by hype and overlook whether a solution is actually right for your business.

To make it easier for you to sift through the noise, we put together a checklist to help you screen AI vendors and cut through flashy marketing.

Why picking the wrong AI vendor hurts

“If I don’t use AI for my business, my competitors will crush me.” 

Sound familiar? 

The sense of AI FOMO is what’s driving many companies to jump on AI tools without proper vetting or research.

This leads to teams making a hasty decision that wastes months of time, thousands of dollars, and potentially part of your reputation on platforms that underdeliver or mismanage data.

Here are some of the biggest risks of choosing the wrong AI vendor.

Time

Every tool takes time to implement and learn. Choose poorly, and you’ll sink hours into setting up and testing software that ends up being shelved.

Pilots and trials are useful, but only if they’re structured carefully with clear KPIs to watch for. Otherwise, you might walk away with the wrong impression about AI’s potential.

How to avoid it: Set clear success criteria before testing, and measure results against them.

Cost

High-quality AI tools are rarely cheap. Many come with add-on charges for integration, implementation, testing, and maintenance. A bad choice can eat your budget without returning value, which is why you need to review the vendor’s pricing.

That’s why you should model your total cost of ownership. Not just the sticker price.

How to avoid it: Ask vendors for a full cost breakdown, including extras, and model ROI before you commit.

Reputation

Your reputation is your most valuable asset. Choosing vendors that violate data privacy regulations or use biased and unverified data to train their solution may harm your reputation and ruin your customer’s trust.

How to avoid it: Verify compliance certifications and ask how their AI models are trained and monitored for bias.

Common pitfalls in AI vendor selection

Vendor selection is never an easy task. Even seasoned leaders fall into some of these traps, especially since the AI space is still young and full of hype.

Falling for marketing hype

Almost every AI sales platform promises to be “a revolutionary tool that will supercharge your sales process once and forever.” But don’t pull out your wallet just yet. 

Too often, such tools promise more than they can deliver, so you must learn to critically analyze their claims and tell fact from fiction. 

How to avoid it: Look for real case studies, ask for proof of ROI, keep expectations realistic, consult with AI experts before integrating

Ignoring integration needs

A shiny platform is useless if it won’t plug into your core tools. Without a two-way integration, you’ll spend more time moving data than using it.

AI tools need lots of data, so you’ll want to integrate it into your current tech stack to get the biggest bang for your buck. However, some vendors may have limited integration options. 

How to avoid it: Confirm the integration with your core tech stack before signing

Neglecting data privacy and security

Compliance with regulations like GDPR and CCPA is non-negotiable, and skipping this step can be costly.

The dizzying array of features flaunted by AI vendors can leave you feeling overwhelmed. It’s too easy to get drawn in by clever marketing and lose sight of a critical step: Verifying whether the tool complies with the major data regulations and privacy laws.

How to avoid it: Ask vendors about certifications, encryption, and how they train and handle data

Overlooking hidden costs (time & money)

Hidden expenses may include indirect costs of infrastructure set-up, integration, team training, and feature testing. You’ll probably want to get in touch with other teams to better understand the AI integration process, plan your budget, and calculate the ROI.

How to avoid it: Map out the total cost of ownership with input from your tech and finance teams, then compare it against the possible ROI

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Ultimate checklist for screening AI vendors 

With so many platforms fighting for attention, it’s easy to get lost in feature lists and marketing claims. That’s why having a clear, repeatable process for screening vendors is essential. 

A checklist not only helps you compare tools side by side, but also keeps you focused on what matters most: 

• Fit
• Reliability
• Long-term value

Think of this as your roadmap for cutting through the noise. Instead of chasing the “flashiest” option, you’ll be able to zero in on solutions that solve your real business problems, integrate smoothly into your workflow, and deliver measurable ROI.

Research and shortlisting

Before diving into deep research, start by weeding out unverified vendors. 

A quick initial screening will steer you toward authoritative, trustworthy platforms that deliver on their promises. Here’s how to make your initial screening effective:

Review case studies

Find the section with case studies and success stories on the vendor’s website or elsewhere. Look out for the following information:

• Features that provide the most value to their customers
• Specific metrics and ROI (e.g., “The tool helped Company X increase sales by X%”)
• Problems that the tool successfully solved for other companies 
• Cases similar to yours, giving insights into the results you can expect

Visit the websites of the companies featured in success stories to verify their legitimacy. If possible, contact them directly to ask about their experience with the tool.

Analyze client testimonials

Browse Trustpilot, G2, or Capterra for customer reviews. Another idea is searching by keywords in industry-specific Reddit communities where people share their experiences with the tool. 

Check for industry awards and media recognition

Look for media coverage or industry reviews, as these give extra points to the company’s reliability. Interviews with founders, if available, will help you better understand the product’s value, main features, and potential.

Look out for the red flags

Stay away from the companies that badmouth their competitors. It’s a clear sign of immaturity and unprofessionalism. 

Another red flag is when a company claims to be “the only one on the market” or “the best in the industry.” Always dig deeper and compare their features and performance with competitors to separate hype from reality.

Evaluating technical fit

Different technologies address different needs. Always start by defining your specific needs and use cases. Identify the most pressing business problem you want to solve with the help of AI and only then analyze the actual tools. Here’s how to assess if the solution is the right technical fit:

AI models used by the vendor 

The more advanced AI models the platform uses, the more possibilities you will get. Some platforms allow you to customize the AI models to your unique business needs. For example, AiSDR lets you choose from several OpenAI and Anthropic models to better serve your outreach goals.

Integrations

Make sure the platform integrates with your sales tools: CRM system, email software, data and analytics, or accounting solutions. 

Scalability

The platform should be able to adapt to the increasing volumes of leads and sales as your business grows. For example, if you’re looking for an AI lead database, make sure that the contact list updates automatically and that workflows are dynamic and can be personalized. 

Performance metrics and benchmarks

Check the data insights and analytics the platform provides. For advanced data analysis, choose the platforms with predictive analytics and forecasting.

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Automation capabilities

Determine exactly what this platform can automate and if it aligns with your immediate needs. Make sure automation will improve your sales processes and free up your team to focus on high-value activities. Here’s what you should look for:

• Can the platform automate repetitive tasks like following up on emails or scheduling meetings?
• How customizable are the automation rules?
• Are there any limitations regarding the volume or complexity of tasks that can be automated?
• How does AI automation assist in lead prioritization, scoring, and routing?
• Can the tool generate personalized messages?
• How well does it adapt to your industry-specific sales needs?

Data security and compliance

Verifying these two aspects is critical. A vendor with weak data protection could expose your customer data to breaches, damage your reputation, and lead to serious legal consequences. Here’s what you have to review:

Data handling and privacy measures

Ask about the platform’s security measures to keep the information private and inaccessible to unauthorized third parties. Such measures may include access controls, sensitive data encryption, and regular security audits and checks. Find out how the platform collects your data and who can access it.

Data protection protocols

How does the platform handle data security? Confirm whether it uses data encryption protocols and how they protect customer data. Check for data maintenance and backup procedures in case of customer data loss.

Regulatory compliance 

A truly reliable platform not only complies with data regulations in your country but protects your own compliance. For example, Apollo allows you to remove all prospects located in the EU from prospecting and email lists.

Security certificates 

Make sure that the platform complies with the security standards and has all the necessary certifications, such as ISO 27001 and ISO 27701. Usually, you can find this information in the Security section on the vendor’s website.

Data ownership and rights

Read the company’s terms of service to verify that you retain all the rights to the customer data and that no ownership is transferred to the platform.

AI training data and potential biases

Find out what types of datasets the platform uses to train its data. A narrow dataset might only represent certain groups of people, resulting in biased recommendations. Remember to ask what algorithms the vendor uses to detect data biases.

Vendor background

We’ve already mentioned reviews and success stories, but here’s some extra information worth exploring.

Company history, funding status, and financial health

Find the company’s profile on Crunchbase, CB Insights, AngelList, PitchBook, or Owler and search for information about funding rounds, the total volume of investments, and company history and stability.

Client references 

For client references, check out the company’s website as well as G2, Capterra, Clutch, or Product Hunt. You can also reach out to their current or past clients via LinkedIn or professional networks to ask about their experiences.

Team expertise and credentials

If you want to learn more about the team behind the product, start with the About Us and Team pages, and don’t forget to explore their LinkedIn profiles to review their educational background and work experience. Websites like Checkr and GoodHire can help you verify the employees’ education, certifications, and past employment claims.

Developmental roadmap

To understand the company’s priorities and plans, check out its What’s New or Updates pages, find its press releases or news articles online, or even join community forums where the company communicates with its users.

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Implementation and support

To learn more about how the company handles implementation and support, check out the following information on its website or during the introductory call.

• What is the onboarding process and the barrier to entry?
• Does the vendor provide any training resources and support?
• Is there updated technical information?
• What is their customer support policy?
• Do they provide maintenance?

Cost analysis

While most AI vendors operate on subscription models, extra costs can often sneak in. Here’s what to watch for when analyzing the prices.

Pricing model

Find out what payment model the company uses: subscription, user-based, or credit-based. 

Free trials are useful for testing basic functionality, but not all AI vendors offer one since actual costs are incurred by platform usage.

In this case, consider platforms that offer monthly contracts so that you can test and unsubscribe with minimal friction. It’s also a red flag if vendors want to lock you into a multiyear contract after a 3-month paid trial. This is a sign that they’re aware that their product isn’t consistently performing.

Credits

If the company uses a credit-based system in its plans, clarify what “credit” means, how many credits the platform charges for different actions, how to check your credit balance, when credits renew, and if you can purchase additional credits if needed.

Customer support

Is customer support included in the price? Can you get help with tech issues via customer support, or will you have to hire external experts for an additional fee?

Hidden costs

Be sure to check for any hidden costs beyond the subscription price. These may include expenses for implementation, customization, scaling, data cleaning, hardware upgrades, or migration.

ROI potential

Return on Investment is a special formula that calculates the cost and the benefit of an investment. The higher your AI software’s ROI, the better it works for your budget and requirements.

To calculate potential ROI, use the following formula:

ROI = (Net benefit – Total cost) / Total cost * 100)

For example, you can add up the costs of labor for all tasks you want to automate (e.g., lead generation or content writing), subtract the cost of automation, and then divide this number by the total automation investment. If the ROI is positive, you can safely invest in this tool, as it will pay off.

Time to value

Time to value is also part of potential ROI, and here’s what it includes:

Implementation timeline

How long will it take to deploy the solution and start seeing results? It’s best to consult a tech expert with hands-on experience in platform transitions. They know the intricacies and can provide an estimated timeline for your case.

Breakeven point

How long will it take for the benefits to outweigh the costs? You might want to speak with people in your niche working with this AI vendor and ask when they’ve started seeing results.

Intangible benefits

Does the tool improve team/customer interactions or satisfaction? A tool that improves customer loyalty will also impact your ROI, bringing in higher revenue and new clientele drawn by positive feedback.

Contract terms

Inquire about contract terms to avoid vendor lock-in. Vendor lock-in happens when you become overly dependent on a specific AI vendor, making migration to another vendor too costly, time-consuming, and labor-intensive. To avoid it, ask the following questions:

• How can I export all my data if I decide to move to another tool? In what formats can I export it?
• What is the cancellation policy?
• Can I use only the features I need?
• Ask about contract terms and exit clauses. What is the minimum contract length, and are there penalties for early termination?
• Is your solution modular? Is there an option to use only particular features?
• Do you provide support for migration if we decide to switch vendors?

Demos 

The purpose of a demo is to demonstrate the platform’s capabilities and customization and integration options. We recommend having your sales team members present during the demo so they can ask specific questions and see if the platform is a good fit for their needs.

Here’s what to focus on during the demo:

• Is the interface intuitive and easy to navigate?
• Can the platform features be customized to your unique needs?
• Does the platform directly address the challenges you face in your sales process?
• Can the platform automate repetitive tasks?
• How customizable are the automation rules?
• Can the platform handle an increase in team size, leads, or data volume as your business grows?
• What type of onboarding and training does the vendor offer?
• Can you share examples of how other businesses in our industry use this platform?
• How does the platform ensure data accuracy and avoid bias in AI recommendations?

Next, ask the vendor to demonstrate how the platform handles specific use cases from your business, such as:

• Managing inbound leads
• Automating follow-ups
• Generating sales performance reports

This gives you a more complete picture of how well an AI vendor will meet your needs.

Checklist: AI vendor screening