What do you do if your stakeholders and clients don't understand the value of AI?

There are many ways to demystify AI and demonstrate value for your clients & stakeholders. Here are a few ideas: - Start with Success Stories: Share successful AI use cases with measurable outcomes. LinkedIn is a great place to find AI case studies. - Think About AI Use Cases: Talk about specific AI use cases for your business, like Generative AI for marketing, AI-powered chatbots for better customer service, or AI optimized HR policies, procedures and job descriptions. - Demonstrate Potential ROI - Establish benchmarks for current KPIs and projected ROI from new AI programs. - Bring in Outside Expertise: Consider hiring an AI consultant to help fill in gaps and identify additional opportunities.

If you are like me, you are pretty excited about AI and tech. However your stakeholders are going to be less interested in the tech and more interested in solving the problem. So start on the problem, ask "what happens if we don't solve the problem in the next 6 months? What could the cost impact be to the business?" This will agitate the problem into a tangible financial metric that can be used to 1) support a business case 2) determine it is worth pursing to solve. Then ask, "What if there was a way, we could solve this faster than before, at a higher quality and consistency and with less cost? Would that be worth exploring together for 15mins?" You should get a YES to that question. Then book time to show how to use AI to solve it.

Problem: Companies struggle to accurately predict customer churn, leading to loss of revenue and market share. They lack insights into customer behavior patterns and fail to proactively retain at-risk customers. This results in decreased customer satisfaction and increased marketing costs. 📉 Solution: Our AI-powered churn prediction system analyzes vast amounts of customer data, identifying early warning signs of potential churn. By leveraging machine learning algorithms, it predicts which customers are likely to leave and provides actionable insights for targeted retention strategies. This empowers businesses to intervene effectively, reduce churn rates, and maximize customer lifetime value.

Here in Germany, when I mention AI's potential, many leaders think it's still far off, just a science-fiction novelty. But consider this: 'Missing the AI wave today is like ignoring the internet's rise in the '90s. We risk playing catch-up later.' My approach? 'Let's identify one process in your business that's slow or costly. With AI, we can streamline it, making your operations smoother and more efficient. This isn't about futuristic dreams—it's about solving today's problems with tomorrow's tools. Let's lead the innovation, not follow. Then i show up with tailored use-cases and show'em what is possible today and there I mostly got em ;)

Avoid getting overly technical. Instead, translate AI capabilities into tangible benefits that solve their problems or improve their bottom line. This focus on real-world outcomes is helpful. However, you might disagree if you believe a basic understanding of the tech is necessary for informed decision-making. An example would be highlighting how AI can streamline customer service rather than focusing on specific algorithms.

When stakeholders and clients don't grasp the value of AI, it's crucial to start by clearly articulating the problem AI can solve and how it aligns with their goals. Demonstrate tangible results and the potential impact AI can have on efficiency, cost savings, and innovation. Address any risks or limitations transparently to manage expectations. Involve stakeholders in the AI development process, soliciting their input and feedback to foster buy-in and ownership. Educate them on AI capabilities and empower them to make informed decisions by providing training and resources. Additionally, ensure ongoing communication and collaboration to build trust and drive successful AI adoption.

Did you know that communicating at 5th grade level is found to be the most influential? Even at presidency level? We all want to sound smart so use industry language which our clients might not be following. So if you use "tech language", that might be what's causing the problems with your stakeholders. Remember: Most conflicts arise because there is a communication problem between you and your clients/stakeholders. Use simple language and watch the magic unfold

Articulating the problem and the solution in relatable terms not only ensures alignment with your stakeholders' objectives but also builds trust and confidence in the AI solution you propose. By demonstrating a deep understanding of their needs and how AI can meet them, you turn abstract concepts into tangible benefits

Bridge the knowledge gap: Focus on specific benefits: Highlight how AI addresses their pain points (e.g., cost reduction, efficiency gains). Showcase success stories: Present real-world examples of AI achieving similar goals in their industry.

When stakeholders don't grasp AI's value, explain how it solves their pain points in relatable terms. Highlight tangible benefits like cost savings or faster decisions using examples they understand. Build confidence, share case studies, quantify impact through metrics. Visualize data effectively. Address risks transparently - data privacy, bias mitigation strategies, ethical principles. Explain safeguards like secure data handling. Involve them throughout - gathering requirements, testing, refining. Their participation breeds ownership. Invest in change management - training, documentation. Empower them to utilize AI as an augmentation tool. Clearly articulating value and making stakeholders partners turns apprehension into enthusiasm.

By leveraging AI, we've achieved remarkable results 📈. Our solution has significantly enhanced efficiency, reducing processing time by 40% compared to traditional methods. Moreover, it boasts an impressive accuracy rate of 95%, surpassing industry standards. 💯 This translates into substantial cost savings, estimated at $500,000 annually. 🤑 Additionally, customer satisfaction has soared by 30%, thanks to personalized recommendations driven by AI algorithms. 🎉 Furthermore, our solution has unearthed valuable insights from data, enabling proactive decision-making and identifying new revenue streams. 🚀 Overall, our AI implementation has proven to be a game-changer, delivering tangible benefits and driving innovation in our operations.

In my opinion, the key to discussing AI project outcomes, especially with stakeholders who may feel apprehensive at the mention of 'AI', lies in emphasizing specific metrics such as reduced response times, increased conversion rates, or lowered operational costs, tailored to the particular needs of their industry. It's also beneficial to highlight the security and reliability, focusing on those recognized for complying with high-security standards, which assures stakeholders of the safety and integrity of their data. By incorporating success stories and case studies from related fields, this strategy becomes even more effective.

To demonstrate AI's value, focus on tangible results and impacts. Utilize data, metrics, and visuals to showcase improvements in performance, accuracy, and efficiency. Make a compelling case by comparing these results against previous benchmarks, alternatives, or industry norms. Highlight how the AI solution contributes to significant savings in 'energy' (time, $ , or resources), boosts revenue, enhances customer satisfaction, or improves quality. I know it's tempting to focus on the tech's features and specs. If I could go back in time to every time I thought that would work and stop myself, I would. it never lands as well as you think it will. Focus on the benefits to THEM and the outcomes, it'll make your valueprop unmistakably clear

In my opinion, demonstrating the results and the impact of AI is a powerful way to convey its value. This could involve sharing case studies of other businesses that have successfully implemented AI, or even better, conducting a pilot project within the client's own business. Seeing the tangible benefits of AI in action - whether it's improved efficiency, cost savings, or enhanced decision-making - can be a game-changer in their understanding and acceptance of AI.

Being able to provide a concrete and relatable example with no development time is a great way to show how AI can be used. I just recently did this with a potential client. They know about AI and are highly technical but I could tell they were not sure about the use of AI in the application, maybe they've already been burned or simply just have overwhelming seen text and code generation when we were talking about something more specialized. After the call I was able to create synthetic data replicating their actual use case, create the prompt including a structured output definition that is representative of the required outcome, and execute in ChatGPT. With the outcome, I could share the conversation and they were impressed. 30 minute MVP.

With AI, show is always, always, always better than tell. It's a new concept. It's a vague term. And it means different things to different people. So it's no wonder clients and management teams are sceptical, worried, or hesitant. They need to see, with their own eyes, how AI can: - Do the task they're interested in — to a reasonable quality - Do the task safely and not create new problems — like making up facts - Do the task quickly and cost-effectively - Drive genuine productivity improvements in their teams With those points in mind, you need to: 1. Choose the task you think AI can have a large impact on 2. Create a simple proof of concept, e.g. Zapier 3. Simulate 5-10 examples of this task 4. Show a comparison of the results

I prioritize demonstrating tangible results and impactful outcomes. By showcasing successful AI projects and their direct impact on key metrics such as efficiency, cost reduction, and revenue growth, I provide concrete evidence of AI's value proposition. Utilizing data-driven insights and case studies, I highlight how AI-driven solutions have addressed similar challenges in other industries or organizations, resonating with stakeholders' objectives and pain points. Through tailored presentations and interactive sessions, I facilitate a deeper understanding of AI's potential to drive transformative change and unlock new opportunities for business growth and innovation.

In my experience, demonstrating the capabilities of AI is an effective method to alleviate concerns. A lot of the apprehension comes from headlines and news stories about AI being misused. Some people are simply cautious about embracing new technologies. Yet, when provided with opportunities to see AI's potential in action, emphasizing safety and best practices, the response is often one of awe. Audiences frequently express their amazement aloud, indicating a shift in perception from viewing AI as daunting and unfamiliar to recognizing it as approachable and practical.

Reports and insights always grab stakeholders' and clients' attention, which is important to show them practical demonstrations or case studies of AI solutions in action. Seeing tangible results can help stakeholders grasp the value more effectively.

Show AI's impact via metrics, visuals; compare to standards. Highlight time/money savings, revenue boost, innovations for convincing results.

In deploying AI, it's crucial to acknowledge and mitigate risks. 🛡️ We prioritize data quality, employing rigorous validation methods to ensure accuracy and reliability. 🔍 Privacy and security are paramount; we adhere to strict protocols and encryption standards. 🕵️♂️ Regular monitoring detects errors and anomalies swiftly, triggering prompt corrective action. ⚠️ Addressing bias and promoting fairness is central; we employ diverse datasets and algorithmic checks. 📊 Our ethical framework guides decision-making, ensuring alignment with societal values. 💼 Continuous updates and maintenance enhance system robustness and scalability. 🔄 Transparency and accountability are integral; we engage stakeholders, fostering trust and confidence.

Transparency about AI risks demonstrates responsibility and builds trust. Addressing challenges like data quality and bias upfront reassures stakeholders of careful management and reliability.

One thing I found helpful when addressing the risks and limitations of AI is to be upfront and honest. AI is not a magic bullet that can solve all problems, and like any technology, it has its limitations and potential risks. These could include issues around data privacy, the need for high-quality data, or the risk of over-reliance on AI at the expense of human judgment. By acknowledging these concerns and discussing how they can be managed, you can build trust and credibility with your stakeholders and clients.

Working in healthcare security risk is always on everyones' minds. Being in data, I have been starting with 2 application layer requirements: row-based access control on RAG and column/attribute filtering on data stores. In RAG, row-based access control ensures that when working with patient data there is no cross-contamination so we can have a high degree of confidence that the data being used as context only belongs to a single patient of interest. The column/attribute filtering ensures that while we have a lot of data available, we only allow data to be used that the end user has authorization to access. Putting these guard-rails before output generation is critical for ensuring there is no leakage of secure patient information.

Addressing stakeholders' lack of understanding requires clarifying AI's technical intricacies. Utilize analogies to simplify complex concepts, such as comparing AI algorithms to a team of expert advisors providing insights. Highlight the technical advantages, like AI's ability to process vast datasets swiftly, leading to more informed decisions. Engage stakeholders in technical discussions to foster understanding and build trust.

It's essential to openly address the potential risks and limitations associated with AI, such as data privacy concerns, implementation costs, and the need for ongoing maintenance. Being transparent about these challenges and how they can be mitigated fosters trust and sets realistic expectations.

Abordar riscos e limitações da IA é fundamental para conquistar confiança. Eu sempre enfatizo que, embora a IA prometa transformações, ela não está isenta de desafios. Discuto abertamente sobre como lidamos com a privacidade dos dados, a segurança e a mitigação de preconceitos, garantindo que essas preocupações sejam parte integral da nossa estratégia de desenvolvimento e implementação. Além disso, apresento nosso plano de manutenção contínua e atualização da IA para adaptá-la às mudanças do mercado e às necessidades dos clientes. Esse nível de transparência e preparação mostra que estamos comprometidos em fornecer uma solução de IA não apenas avançada, mas também segura e ética.

Be transparent about potential risks (data privacy, bias) and the limitations of AI models. Proactively discuss strategies to mitigate these risks, build trust, and establish realistic expectations.

Identifying risks and limitations early in the process of change allows for a clear mitigation of those risks. It's important to start by strategically aligning on an outcome with all stakeholders, and communicating all possible risks and limitations to the solution. Once these have been identified, they can be correctly mitigated in the future state with clear expectations for the AI solution.

Building trust in your AI solution involves acknowledging its potential risks and limitations. A key aspect is understanding the context of use, especially with generative AI tools. It's vital to assess if the intended use can accommodate errors and whether the user has the expertise to correct them, ensuring risk mitigation.

Show don't tell! Your clients were taken advantage of by many vendors so no matter how impressive your pitch is, they are listening to it with skepticism so that's not the best way to win them over. Show them examples of how using AI will change the solution at a way faster speed or way better. Show them case studies of other clients you implemented those solutions to. Show them industry case studies Showing them instead of telling them will make them feel part of the process as well as making them see it themselves. Try it!

To foster stakeholder and client engagement with AI, involve them from inception 🌱 to deployment 🚀. Solicit their input, feedback, and suggestions throughout the project 🤝. Demonstrate how their needs and values shape AI design and decision-making 🎨. Encourage their participation in testing and validation phases 🧪. By making them active participants, stakeholders feel valued and invested in the solution 🤝. This collaborative approach builds trust and comfort with AI technology 💡. It transforms stakeholders from mere end-users to integral members of the team 🙌, ensuring the AI solution aligns closely with their expectations and requirements.

Like any good partnership, bring them along for the journey! In our case, we are implementing an advanced digital assistant to support our employees with their HR needs. Employees don't care or want to distinguish what is an HR issue verses what is an IT, or Facilities, or Finance matter, do they? So we brought those stakeholders along with us as we evaluated vendors and imagined the possible. They may not be ready to adopt when you are, but they will appreciate the front-row seat.

Involving stakeholders and clients in the AI development and deployment process is key to building comfort and trust. Engage them by seeking their input, feedback, and suggestions throughout various project phases. IME, this demonstrates how their needs, preferences, and values are integral to your AI design and decision-making. Offer opportunities for them to test, validate, or refine the AI system, making them feel like active contributors rather than just passive recipients. This collaborative approach not only enhances the AI solution's relevance and effectiveness but also fosters a sense of ownership and partnership, ensuring the end product truly resonates with their expectations and goals.

I adopt an inclusive approach by involving them in the AI process. By inviting them to participate in workshops, demos, and pilot projects, I provide firsthand exposure to AI technologies and their potential benefits. This hands-on experience allows stakeholders to gain a deeper understanding of AI's capabilities and relevance to their specific needs. Additionally, soliciting their input and feedback throughout the process fosters a sense of ownership and collaboration, leading to greater buy-in and alignment with AI initiatives. Ultimately, involving stakeholders in the AI journey empowers them to recognize and appreciate its value in driving organizational success.

Involving stakeholders and clients in the AI implementation process can also be highly beneficial. This could involve inviting them to brainstorming sessions, seeking their input in decision-making, or involving them in testing and refining the AI solution. This not only gives them a sense of ownership and control, but also provides a hands-on experience of how AI works and the value it can bring.

Involving stakeholders and clients in the AI implementation process can increase buy-in and understanding. This includes seeking their input during the planning phase, updating them regularly on progress, and incorporating their feedback. This collaborative approach ensures the AI solution aligns with their needs and concerns.

One time at work, to ease AI skepticism, we involved stakeholders and clients throughout the AI project's lifecycle. Their feedback influenced the solution, fostering a sense of collaboration. This approach made them active contributors, enhancing their commitment and comfort with the technology, showcasing the benefits of involving stakeholders in the development process.

Incluir stakeholders e clientes no desenvolvimento da IA é uma estratégia que sempre emprego para alinhar expectativas e aumentar a aceitação. Realizo workshops e sessões de brainstorming para colher insights diretamente da fonte, garantindo que o projeto reflita suas necessidades reais e aspirações. Também os convido para participar de testes piloto, oferecendo uma visão interna do processo e permitindo que experimentem os benefícios práticos da solução em primeira mão. Essa abordagem colaborativa não apenas enriquece o projeto com diversas perspectivas, mas também transforma os participantes em defensores da solução de IA, pois eles veem seus próprios inputs e preocupações refletidos no resultado final.

Involving clients is key since they are the expert in their field, best placed to point out what features the model could use. Also, I've found that presenting results visually makes a huge difference. It simplifies understanding and fosters a stronger collaboration.

Empowering stakeholders and clients with AI knowledge is vital. Offer comprehensive training 📚 and support to foster understanding and confidence in utilizing AI solutions. Equip them with skills 🛠️ to interpret outputs and leverage capabilities effectively. Emphasize AI as a complement to their work, not a replacement, fostering a collaborative mindset. 🤝 Provide guidance on interacting with AI systems and highlight its potential to enhance productivity and decision-making. Encourage an environment where AI is perceived as an ally rather than a threat, fostering enthusiasm and adoption. Through education and empowerment, stakeholders can harness the full potential of AI, driving innovation and success in their endeavors.

Managing the impact of AI on your organization encompasses both maximizing its benefits and mitigating potential challenges. It's crucial to have a comprehensive understanding of how AI influences not just productivity and efficiency, but also workplace dynamics and ethics. Implement regular assessments to evaluate the effectiveness of AI applications and their alignment with business objectives. Be proactive in addressing workforce concerns related to job displacement by offering retraining programs and highlighting new opportunities created by AI. Furthermore, prioritize transparency and ethical considerations in your AI initiatives to build trust among stakeholders.

Finally, I initiate targeted training sessions, workshops, and informational materials tailored to their specific needs and knowledge levels. By providing clear explanations, real-world examples, and case studies illustrating AI's impact, I aim to demystify the technology and showcase its potential benefits. Additionally, I offer ongoing support and resources to encourage continuous learning and exploration of AI solutions. Through these efforts, I empower stakeholders and clients to make informed decisions and fully leverage AI to drive business success.

Education is key to empowerment. Offer workshops, webinars, and resources that explain AI's principles, applications, and benefits in their context. The more knowledgeable stakeholders and clients become about AI, the more likely they are to appreciate its value and advocate for its adoption.

Educating and empowering stakeholders and clients is another crucial step. This could involve providing training sessions, sharing educational resources, or organizing workshops with AI experts. The goal is to equip them with the knowledge and skills to understand and use AI effectively. Remember, the aim is not to turn them into AI experts, but to give them a sufficient understanding to make informed decisions and feel comfortable with AI.

If your stakeholders and clients don't see the value of AI, it's crucial to shift their perspective through education and empowerment. Simplify the complex, showcase success stories, highlight AI as a collaborative tool, and focusing on practical benefits throughout your discussions are ways to ensure everyone is on the same page. Help all stakeholders understand the art of the possible through education, and how AI can truly impact their daily lives.

Educating and empowering stakeholders and clients is crucial in maximizing the adoption and impact of your AI solution. If a tool isn't being used, it often points to a gap in communication or a misalignment with the initial problem it aimed to solve. Providing comprehensive training, guidance, and support helps users understand, use, and fully exploit the tool's capabilities, ensuring it enhances rather than replaces their work. By demonstrating how AI serves as a powerful ally in daily operations, users are more likely to embrace the technology and become advocates for its benefits, ensuring the longevity and success of the solution.

It all starts by demystifying AI. Begin with the basics, educate them on what AI is and how it works, use simple language and give real world examples on how it is already in use. Next, explore and share success stories from similar industries where AI has driven significant benefits, such as improved efficiency in manufacturing, increased sales, targeted marketing, AI chatbots etc. Remember the goal is buy-in.

I simplify AI's benefits by linking them directly to stakeholders' or clients' challenges, avoiding jargon. By showcasing clear examples and successes, I make the abstract tangible. Demonstrating AI’s impact through data and visuals, I focus on outcomes like efficiency gains and cost reductions. I'm upfront about AI’s limitations and our mitigation strategies, fostering trust. Involving them in the development process ensures their feedback shapes the solution, making them partners, not just users. By educating and empowering them with the knowledge to use and benefit from AI, I demystify technology, showing it as an augmentative tool, not a replacement.

Educar e capacitar stakeholders e clientes é uma estratégia que priorizo para construir uma base sólida de compreensão e apoio à IA. Organizo sessões de treinamento e workshops interativos, onde desmistifico a tecnologia IA, apresentando-a de maneira acessível e prática. Foco em como a IA pode ser uma ferramenta valiosa para ampliar suas capacidades, não para substituir o toque humano. Além disso, forneço materiais de apoio e guias passo a passo para que possam consultar e se familiarizar com a solução no seu próprio ritmo. Esse processo de capacitação transforma a incerteza em confiança, ajudando-os a perceber a IA como um complemento valioso para suas atividades diárias.

To help stakeholders and clients see the value of AI, simplify AI concepts and use relatable examples and case studies showing real benefits like cost savings and improved efficiency. Conduct hands-on workshops to demonstrate AI's practical applications, linking it directly to their business goals. Highlight AI's competitive advantages and address any concerns about ethics and data security. Consider starting with small pilot projects to provide a tangible sense of AI's potential. Share success stories from the industry to underscore AI's strategic importance in enhancing business performance.

If your stakeholders and clients don't understand the value of AI, you have a strategic decision to make. One approach is to invest time and effort into educating them. Share compelling examples, send relevant articles, and offer to build a proof-of-concept. By helping them "see the light," you position yourself as a trusted advisor and can build strong, long-lasting relationships. However, this process can be time-consuming, and success isn't guaranteed. Another approach is to focus on clients who already recognize AI's value. By targeting these organizations, you can boost their AI adoption and achieve rapid results. This strategy allows you to build a portfolio of successful AI projects and establish yourself as a go-to expert.

I would suggest to have a value conversation. Stakeholders and clients will value AI 🤖 if they see actual benefits and impact. I would not try to have technical explanations to all stakeholders I would rather being transparent about the role of AI and the role of people and how this combination creates more value

Before embarking on the path of advocating AI solutions to stakeholders, ensure a clear understanding and genuine value of AI for them. Embrace the critical lens towards potential hype, willing to introspect and reassess your stance if the proposed value is met with skepticism. Recognize that not all tasks benefit from AI integration; some may even entail undue risks under the guise of efficiency. Should the value of AI be undeniable, articulate it with clarity and precision, avoiding the pitfalls of overpromising or resorting to overly enthusiastic language. This approach not only fosters trust but also aligns expectations realistically.

Consider tailoring communication to address fears, showcasing tangible benefits of AI, engaging stakeholders frequently, and using clear examples to build trust and understanding.

There are lots of options in this case: education, training, exposure to similar orgs who've attempted or implemented AI for reference, etc. But this is also a time where we can focus on the outcomes and goals, and should AI be a component that helps achieve those goals, look at ways to insert it into the solutioning process without it being overwhelming. AI is used as a label on components of almost all solutions out there today. With all that noise, it can be scary or seem like a big leap. Reminding ourselves of the good ol' "fail fast" approach, we can look to build proof of concepts that provide the results sought. And then bring them along that journey should it be successful.

People form quick impressions on broad topics. Instead trying to shift popular perceptions on "AI's value", (which would take years) we look to focus first on the value of solving specific problems. By identifying these issues (like losing leads due to slow responses) it becomes much easier to show how AI can outperform traditional methods in a faster, cheaper, and more efficient way (by handling conversations, booking meetings, rebooking, freeing teams for more opportunities.) Questions certainly remain, (like how can we personalize this to our playbook to ensure the perfect experience) but focusing on solving business challenges together sidesteps broader debates for more productive, impactful discussions.

Focus on understanding and articulating your client's problem - AI may not even be the right solution. As I always say, "don't use AI like a hammer in search of a nail." But when you find that nail, hit it hard.

Lastly, consider the broader ecosystem in which your stakeholders and clients operate. Encourage them to look at industry trends, competitor activities, and market demands that underscore the importance of AI. Highlighting the strategic advantage AI offers can motivate them to embrace these technologies as essential tools for innovation and competitive differentiation.

One thing I found helpful in helping clients and stakeholders get comfortable with using AI tools, is to first help them think about their current workflow and process. Think about each step, action, and time that it takes to get that task completed. Then I take one of the things that they are using, (i.e. writing marketing emails) and show them how to use an AI tool to reduce the work with strategic prompting, based on the steps they outlined. I think it’s helpful for people to think about their process and then show how the process can be more efficient. Everyone loves to save time and effort, and it’s important to emphasize the current effort that is being put forward in order for them to truly see the benefits.