How do you sell artificial intelligence to clients?

One of the first things to check? Is to determine if they even need AI. Many AI use cases can be solved by non AI or ML solutions. Often clients needs are already using an non-AI solution. They see AI as means to automate or make it better. Explore other options before suggesting AI, especially if its more effective. AI takes lots of work from infrastructure to devleopment. So a non-AI solution may be more effective.

First Rule: Don't force it! Many AI initiative fails because of not checking the System and Process readiness. Understanding of client's business and processes is very crucial before jump into a conclusion. If the client has not matured their data practices and advanced reporting, there is no point of selling the AI . AI is only a Cross sell or Upsell thing in most of the cases.

If you don't understand the mission - then don't start an AI journey. A shallow consideration of people, process, technology, business strategy and change management completed. And the end 'why' always kept in mind too. There are many pain / opportunity points e.g., shareholders, stakeholders, organisation, function and individual as all are going to be impacted needs considered. AI can create a lot of value but know the mission, get expert guidance and remain focused to enable you to deliver a successful program.

You want to dominate market in AI. First arm yourself with capabilities. 1. Identify as many use cases as you can - This will help you be prepared for contingencies and become a one stop solution. 2. Consider all the factors impacting the AI service - This includes the company's offerings, its partners, the client's existing infrastructure, the competitors, and some other miscellaneous parameters. 3. Prepare a comprehensive AI policy - Ensure its responsible and sustainable deployment 4. Define clear metrics - Prepare a roadmap to accomplish these metrics through relevant experiments and demos

If you cant explain it, then you don't understand it. AI teams need someone who speaks AI and business. A change / communication management program is not a one off exercise. It is a constant conversation where speaking and listening happen.

Identify AI use cases: Determine the specific AI use cases that align with the client's needs. Highlight how AI can automate processes, improve efficiency, enhance decision-making, or deliver new insights to drive business outcomes. 3. Demonstrate expertise: Showcase your expertise and experience in AI. Highlight successful AI projects you have undertaken, relevant industry knowledge, and your team's qualifications. Provide case studies or testimonials that demonstrate the impact of AI in similar contexts.

Before explaining a solution, it's important to scope it. It helps create better explanations. So many AI and ML projects get lost because building was prioritized over an useable AI product. Focus on the why and what of the solution. Not the how. Focusing too much on implementation too early can cause confusion.

The biggest challenge in selling AI is making it relatable and understandable to prospects/clients. So start by identifying their specific problems and what they hope to achieve. You will want to clearly demonstrate how AI can address their issues and meet their goals using straightforward language and real-life examples. Always take the time to explain how your AI solution integrates smoothly with their existing systems and delivers tangible results. Make sure to encourage questions and feedback to show you’re attentive to their needs. Finally, provide a clear next step, whether it’s a demo or a trial, to keep the momentum going.

Client concerns need to be addressed. The focus on cost-effective, etc. should happen AND the outcomes of the program too. AI can be complex but so can finance, or IT or other disciplines. It is out job to complete great work and explain the why, what and how so everyone remains on the journey to a brighter, augmented future.

Address concerns and risks: Understand that clients may have concerns about AI, such as data privacy, security, or job displacement. Address these concerns openly and transparently, providing reassurance on data protection measures, explaining how AI can augment human capabilities rather than replace jobs, and offering insights into successful AI implementations in similar contexts.

As you continue on in the field, you will find one of the biggest challenges in selling AI is addressing client concerns effectively. Its not unusual for clients to often worry about the cost, security, reliability, ethics, and ease of adoption. So acknowledge these concerns with respect and provide clear, honest answers. You will want to demonstrate how your AI solution is cost-effective, secure, and reliable. Emphasize its ethical considerations and user-friendly design. Try to find a way to reassure them by offering ongoing support, training, and guidance during implementation and beyond. I find that by addressing these worries head-on, you build trust and confidence in your AI solution.

Provide a clear value proposition: Clearly articulate the value proposition of your AI solution. Please focus on its tangible benefits, such as cost savings, increased revenue, improved customer satisfaction, or reduced risks. Quantify the potential return on investment (ROI) and explain how AI can deliver a competitive advantage.

Research and scope. Establish and define a non-AI benchmark to test against. AI is expensive to develop, set up, and test- its experimental. For it to show real difference, it needs to outperform both a non-AI solution and a very simple AI solution. Features and KPIs you are comparing need to be standardized for an effective differentiation.

Its not always easy to make your AI solution stand out from competitors. It starts by emphasize what makes your solution unique and superior. Make sure to highlight your distinct value proposition, competitive edge, and specific features that address your client's needs and goals. Demonstrate why your AI is the best choice with examples of your expertise, experience, and a strong reputation in the AI field. Its smart to convey your passion and confidence in your solution to instill trust and excitement. This approach not only differentiates your AI but also builds a compelling case for why it’s the best fit for the client.

Tight feedback loops are important. Have regular demos to build trust, credibility, and get feedback from your users. Without that, you won't get the right feedback that helps tailor the product. So much of an AI solution is developed through demos. After demos, make sure you schedule user acceptance testing to make sure the AI product answers the business questions.

Provide ongoing support and collaboration: Emphasize that your engagement does not end with the sale. Offer post-implementation support, training, and continuous improvement. Establish yourself as a trusted partner who will work closely with the client to ensure the long-term success of the AI solution.

Understanding client needs is key to selling AI effectively. By clearly explaining how our solution addresses their specific pain points and goals, we can alleviate concerns about cost, security, and reliability. Highlighting our unique value proposition and inviting feedback ensures clients feel heard and confident in their decisions. Finally, prompting them to take action moves the process forward toward successful adoption. Overall, this approach aligns with my perspective on selling AI solutions.

There is no call to action, if you do not know who you are calling! ☎️ Embrace the ACT framework as you call your clients to action. Align their needs with the AI solution, ensuring a clear understanding of the benefits and value. Transparently communicate the urgency and advantage of adopting AI. Provide clear instructions, expectations, and contact details, fostering alignment and clarity. Express gratitude for their time and interest, and follow up diligently until the deal is closed, prioritizing transparency in every step of their AI journey.

Presentation. Invest in it. Learn to make good slide decks that highlight the improvement over the previous benchmarks. Focus on the wins but also highlight areas that are opportunities that can improve the AI models. AI models aren't one-and-done deals. They evolve with the cilents needs.

Clients adopting AI solutions fall into two broad categories - the risk-takers who want to be on the cutting-edge, and the wait-and-see group that moves more cautiously. Some factors that can influence a client's approach: - Industry sector - Some industries like tech and financial services tend to be more prone to adopting new innovations early, while more heavily regulated sectors like healthcare may be more conservative. - Competitive pressures - Companies that fall behind their peers have more incentive to make bold technology moves, while firms leading their markets may be content with incremental change. Other factors include - Risk appetite and culture - Company size - Existing tech landscape

When selling artificial intelligence to clients, I would begin by understanding their specific needs and business goals. I'll tailor my pitch to address how AI can solve their unique challenges and help them achieve their objectives. Using clear and relatable language, I'll explain the benefits of AI without overwhelming clients with technical jargon. I'll provide real-life examples of AI's success in industries relevant to their interests and offer a personalized pilot project or demo to showcase its potential impact on their specific situation. Throughout the process, I'll ensure transparent communication about data privacy and security to build trust and facilitate successful AI adoption.

There is always hype of new technology, case in point, metaverse. From the user viewpoint, its clear from the masses using ChatGPT, that GenAI fills needs that are only limited to the imagination of the user. From the Enterprise viewpoint however, using ChatGPT to support business needs, risks exposing customer data and losing competitive advantage, not to mention regulatory penalties, whereas setting up "Private ChatGPT" will take time to train and deploy inference systems. In short, in the next season of GenAI, it will soon be clear if its a hype technology for Enterprises that will sink into the chasm of unfulfilled promises, over-budgets and overdue projects, or a wunderkind tech that will bring us to a new level of human progress.

Focus on calculating ROI - show the numbers Show how profitable the implementation can be for the company. Find related case studies or focus on generating one of your own. Even the most advanced AI solution will not be convincing if you do not show the clear business benefits that can be used by the Business decision-makers to calculate ROI.

Assess the maturity of the client to adopt AI and accordingly position the solution. Maturity from following aspects: Level of process digitization, quality of data, experience with AI technology, availability of skills, security infrastructure are few aspects.