If you're an executive who wants to leverage artificial intelligence (AI) to boost your business performance, you need to find a reliable and competent AI vendor. But how do you navigate the crowded and complex market of AI solutions and providers? Here are some tips to help you choose the right AI vendor for your needs and goals.
Before you start looking for an AI vendor, you need to have a clear idea of what problem you want to solve with AI, and what outcomes you expect to achieve. This will help you narrow down your options and focus on the vendors that offer the most relevant and effective solutions for your specific challenge. You should also consider your budget, timeline, data availability, and technical readiness for implementing AI.
70% of digital transformations fail (Mckinsey/BCG /Bain etc). AI will go down the same route if companies throw money at buying AI as a product to fix a problem. The problem is people - without the organisational approach of aligning AI to business objectives, helping people change to embrace it, hiring the right talent, listening to expertise (often younger generation) dealing with structure of decision making, evaluating, course correcting etc., AI 'products' bought from a vendor cannot succeed. Predictions are that the spend on AI will be $300bn by 2026 (IDC). There's a lot of vendors waiting to take your money - don't waste it by focusing just on products and not on the organisational challenges
Ask "WHY" Five Times AI solves problems. Why are we looking to use AI? What business outcome do we want to improve (increase sales, reduce costs, improve customer experience)? Keep drilling down until you find the root problem.
Start with what your pain point is and what you think you need to solve it. Many of my clients in AI have no idea what it is they're trying to solve for in the beginning. They just want an AI solution. That is not the right approach and will lead to immensely high sunken cost. Find your pain point, research the vendors, narrow it down to 5, and interview THEM. Meaning look for POC's, how much have they built out their CS team, how attentive will they be to your needs, etc. Remember, the service after the sale is where the top AI vendors will separate themselves from the others. Some of the best ones are the smallest teams in AI. So don't be afraid to work with a startup. Just do your due diligence.
After defining your problem, I'd suggest sitting through some demos or asking for a full feature pilot or trial. Another thing to remember is not just the initial cost - that is what a lot of people tend to look at - but look at the down the road costs of support and maintenance. There could be a low upfront cost to hook you, but if they lock you in long term they could make it up and then some with service maintenance and costs. Additionally AI is a fast moving space, so long-term contracts may not be the best idea. You may need flexibility to move from one AI vendor to another as AI evolves. Most solutions create another problem or challenge, so consider the collateral of the vendor's solution #ai #artificialintelligence #aivendors
If you are looking for a leading vendor of AI toolsets and solutions, at this point it shouldn't be just one vendor. This isn't domain hosting, this isn't file storage, this is a critical, nascent, dynamic domain with rapidly evolving offerings on a monthly basis. If you maintain the "we maintain only one cloud provider" concept and expect that view will meet your AI needs, you may find yourself caught off guard when finding the AI solution that truly makes a difference. Stay nimble at this point.
Once you have defined your AI problem, you need to do some research on the AI landscape and the different types of solutions and providers that exist. You can use online platforms, directories, reports, and reviews to get an overview of the AI market and the latest trends and innovations. You can also ask for recommendations from your network, peers, or industry associations. You should look for vendors that have experience and expertise in your domain, industry, or use case, and that can demonstrate their value proposition and track record.
As stated in the first prompt, do your research but narrow down the list to a Top 3-5 based on your needs. Look for reviews online. But better yet, look at your network and see if a colleague has used any that you're considering and ask them about their experience. Nothing beats a warm referral or reference. Especially with so many AI "solutions" coming out every day.
Part of research in cases like this involve comparative analysis. That said, I would look at how other companies similar to you or your organization may be dealing with the same problem and solving theirs. How did they go about their vendor selection? Not every one will easily share their process, but there are ways to go about getting it... #ai #artificialintelligence #aivendor
Navigating the AI vendor landscape demands meticulous research and discernment. Explore online platforms, industry reports, and peer recommendations to map out potential partners. Prioritize vendors with domain-specific expertise and a proven track record of delivering tangible results. Assess their technological capabilities, ensuring alignment with your project requirements. Most importantly, foster open communication and collaboration, forging a symbiotic relationship for AI success.
Research the AI landscape by staying updated on AI trends and identifying suitable vendors. For example, if seeking an AI solution for customer service, follow industry news, attend webinars, and join tech forums. Then, list vendors offering AI customer service technologies, from large platforms like Google Cloud AI to niche solutions like Drift for conversational AI. Evaluate their technologies, compatibility with your systems, and industry reputation. This approach ensures you're informed and can choose a vendor aligned with your business needs.
Market Survey: Conduct a comprehensive survey of the AI market to identify vendors who specialize in the solution you need. Utilize industry reports, online forums, and platforms like LinkedIn to gather insights. Peer Recommendations: Seek recommendations from peers in your industry who have implemented similar AI solutions. Their experiences can provide valuable insights into the strengths and weaknesses of potential vendors.
After you have shortlisted a few potential AI vendors, you need to evaluate them based on various criteria, such as their technical capabilities, business alignment, customer satisfaction, and ethical standards. You can use online tools, questionnaires, or scorecards to compare and rank the vendors according to your priorities and preferences. You can also request demos, case studies, testimonials, or references to see how their solutions work in practice and how they interact with their clients.
Understand your business needs, and what problems you are trying to solve with the help of AI. Make sure you and the vendor are a good fit in terms of the partnership, and what each party is looking to get out of it near and long term—quality over transactional quantity.
Craft a short list of questions you know you will need to have answered from your new vendor. Make sure they can fulfill those at the very least but also, gauge the quality of the conversation you have with them. Are they too "salesy"? Did they have more than just a salesperson on the call? Are you working directly with founders? Things like that can do wonders for your AI needs.
When evaluating AI vendors look to companies that are focused on the problems you are trying to solve. Many AI companies are taking the shot gun approach trying to offer many different capabilities. At CallRail the phone conversation is critical so we chose a partner that focused on Automatic Speech Recognition (ASR) first. Its the foundation for any other intelligence we want to do downstream so its critical ASR is the best in market. What amazing is I don't feel they are a vendor and are actually true partners. We develop jointly to capitalize on bring more value to CallRail's customers.
Definitely think about if their data and security practice do at least number 1, but better yet both 1 and 2. If your AI efforts are not aligned on data and security, I don't think it will ever work 1. Align with yours 2. Improve yours You can also use vendor comparison platforms and there are many of these. Additionally some companies keep net promoter scores. Examples of vendor comparison platforms include - capterra.com g2.com cbinsights.com #aivendors #ai #artificialintelligence #aisecurity #aidata #datainsights
When evaluating AI vendors, it's crucial to consider their ability to scale solutions and integrate with existing systems. Technical adaptability is key for future-proofing your investment. Additionally, assessing the vendor's commitment to AI ethics, such as transparency in how algorithms make decisions, is essential in mitigating risks related to bias and privacy.
When you have selected the best AI vendor for your needs, you need to negotiate the terms and conditions of the contract, such as the scope, deliverables, milestones, payments, ownership, maintenance, support, and liability. You should also discuss the expectations and responsibilities of both parties, and how you will communicate, collaborate, and monitor the progress and performance of the AI project. You should consult your legal, financial, and technical advisors to ensure that the contract is fair, transparent, and compliant.
Entre los aspectos que se deben abordar en el contrato se encuentran: (i) La definición y el alcance del sistema de IA, incluyendo su finalidad, sus capacidades, sus limitaciones y sus riesgos; (ii) La propiedad intelectual e industrial del sistema de IA, tanto del software como de los datos y los contenidos generados; (iii) Las garantías de calidad, seguridad, fiabilidad y conformidad del sistema de IA con la normativa aplicable; (iv) Las condiciones de uso, mantenimiento, actualización y supervisión del sistema de IA, así como los mecanismos de control, auditoría y evaluación de su funcionamiento y rendimiento; (v) Las cláusulas de confidencialidad, indemnización, resolución de conflictos y extinción del contrato, entre otras.
Know what to look out for is a MUST when looking for vendors and negotiating contracts, especially in AI. Getting a good deal is a must in AI as this space is too fragile for bad deals. Bad deals can kill you. For large contracts smart vendors don't line item. Like me, they would bundle services or features. Otherwise you will spend weeks and months going back and forth haggling over this and that details. If you are going to line item anything, do it with the items that are actually needed like security features, data profiling tools etc. Bundle the rest. That's the way smart vendors sell. #aivendors #ai #artificialintelligence #aisecurity #aidata #datainsights
Make sure you get the best deal for not just you, but the vendor as well. Why? Because you don't want to "beat them up" so much over price that they dread working with you. Yes, they agreed but no one likes working with someone who is only lowest price based. I've worked with several clients that thought they knew more than their vendors and argued over price to no end. Well, like you, your AI vendor probably worked hard on their company and solution as well. So, yes try to get a good deal but remember the value proposition can't be TOO far skewed in your favor. Everything in life is negotiable. Except Apple products ??
When negotiating an AI contract, it's crucial to establish clear KPIs and SLAs to measure the AI system's performance and ensure accountability. Intellectual property rights are particularly important in AI contracts, as they determine who owns the developed algorithms and data. Moreover, given the evolving nature of AI, contracts should include provisions for future updates and scalability to accommodate technological advancements and changing business needs.
Negotiating an AI contract involves clear agreements on deliverables, support, and pricing. For example, if you're implementing an AI system for inventory management, the contract should specify the system's capabilities, such as real-time stock levels and predictive restocking alerts, along with a timeline for rollout phases. It should detail post-launch support, like 24/7 technical assistance and regular updates, plus training sessions for your staff. Pricing discussions should cover the cost of initial setup, monthly or annual fees, and any charges related to usage levels or additional services. This clarity ensures the project meets your expectations, budget, and long-term needs.
Finally, you need to manage the relationship with your AI vendor throughout the lifecycle of the AI project, from initiation to completion and beyond. You should establish regular feedback loops, checkpoints, and reviews to ensure that the project is on track, on budget, and on quality. You should also foster a culture of trust, openness, and learning with your AI vendor, and be ready to adapt and iterate as needed. You should also evaluate the impact and value of the AI solution, and plan for future improvements or enhancements.
They should manage this relationship just as much as you do. Their communication and outreach will be critical. This isn't transactional, like buying a car usually is. It is a relationship built on trust that their solution will help you and you will be a great client for them. Its a true partnership
Think as far as managing relationships, generally a vendor will assign a customer service rep or account manager to each client. But this relationship dynamic never really worked well to me as you have a non-decision maker (at the vendor) reporting to a decision maker (at the client) who is usually a Senior executive that doesn't do the "trench work" You should have equal reporting to equal. Vendor account manager reports to a comparative such as a project manager. The project manager doing the trench work at the client will be much more in touch at the level of which they are actually using the product. If major decisions need to be made on either side, they get reported up #aivendors #ai #artificialintelligence #aidata #aiprojects
Treat It Like a Partnership The best AI vendor relationships aren't transactional. Proactive communication, regular project checkpoints, and open feedback loops make everything run smoothly.
Managing the AI relationship involves close collaboration and open feedback channels. For instance, if you've deployed an AI tool for customer sentiment analysis, schedule monthly meetings with the vendor to review performance metrics, discuss any issues, and explore enhancements. Encourage your team to provide feedback on the tool's usability and effectiveness. This feedback allows the vendor to make iterative improvements, such as refining sentiment detection algorithms for better accuracy. Such ongoing dialogue ensures the AI solution continuously evolves to meet your changing business needs and maximizes the return on your investment.
Once you've chosen an AI vendor, the real work of building and maintaining a productive relationship begins. Throughout your project, from start to finish and beyond, it's vital to keep communication lines open. Set up regular meetings for updates, feedback, and to address any concerns, ensuring your project stays aligned with your goals, budget, and quality standards. Cultivating a relationship based on trust, transparency, and mutual learning is key. Be prepared to adjust and refine your approach as the project evolves. Additionally, continuously assess the AI solution's impact and value, always thinking ahead about potential upgrades or enhancements. This ongoing management and evaluation are essential for long-term success.
When searching for an AI vendor, prioritize trust and transparency. Specifically, w/ GenAI, don't forget this field is still relatively new within a commercial context. Hence, anyone claiming to be an absolute expert might be overstating their expertise. Look for partners who are candid about AI's capabilities and limitations, and who engage in open, collaborative dialogues. Seek those who emphasize shared learning and adaptability, showing willingness to grow alongside AI technology, rather than overselling it. Such a vendor should not only understand your needs but also align with a culture of working together to explore AI's potential, fostering an environment of experimentation, trust, and mutual growth.
Knowledge Sharing Encourage collaboration between your in-house team and the vendors. This builds your team's AI skills and makes future projects even better.
There's always space for those invaluable nuggets of wisdom that don't neatly fit into standard categories. This is your chance to share unique experiences, unexpected lessons, or personal insights that have illuminated your AI journey. Whether it's an innovative workaround, a serendipitous discovery, or a cautionary tale, these pieces of knowledge enrich the landscape of our collective understanding. They remind us that the path to AI success is as much about embracing the unforeseen as it is about meticulous planning and execution.
It should start with a clear definition of your AI problem. Understanding your needs allows you to research the AI landscape effectively, identifying vendors with expertise in your area. My experience has taught me the importance of evaluating vendors based on their ability to understand and align with our goals. Clarity on expectations, costs, and scalability is essential when negotiating the AI contract. Managing the AI relationship means maintaining open communication and being open to adjusting strategies as needed. Also, consider the vendor’s commitment to ethics, data security, and ongoing support. Partnering with a vendor who offers advanced solutions and aligns with your vision and ethics is important.
Choosing an AI provider shall ne be done without a contractual analysis Depending on the AI project at stake, the analysis might be slightly different ! But, in any case, the following articles shall be checked : - liability - intellectual property - personal data processing - confidentiality