What do you do if your sales engineering tasks can be optimized with artificial intelligence?

I use AI almost daily in many aspects of my work. Summarising conversations/recordings. Helping me in content creation. Creating quick scripts / bits of code. It's endless Using AI has helped me sharpen my focus on the high touch / high value work like customer interactions. Embrace the future.

The short answer is: you use it. The most sophisticated sales engineers use AI, and if you don’t, you will be left in the dust. The space is already moving so quickly, and if some sales engineers procrastinate any longer, it will be very difficult to catch up when using AI becomes industry standard. You must keep in mind this caveat, though: you need to do your homework and use AI responsibly. It’s a tool—not a silver bullet that solves everyone’s problems. Check the outputs and make sure they are acceptable work products because, at the end of the day, it’s your name on them, not ChatGPT’s, Claude’s, or Bard’s.

Sales engineering should not always be tedious. By utilizing AI, sales engineering process can be optimized. From company background, customer experience, product knowledge, to sales process, everything will be driven and done not only in quantitively but qualitatively way.

Embracing AI in sales engineering isn't just about efficiency—it's also about personal growth. As AI handles the repetitive tasks, we get to focus more on the creative and strategic parts of our job, making our work more fulfilling. AI's ability to analyze vast data in real-time lets us respond to client needs with highly personalized solutions quickly. It's vital to maintain the human connection; the relationships we build are enriched by AI, allowing us more time for meaningful interactions. Viewing AI as an ally transforms sales engineering into a more dynamic and insightful field.

Utilizing artificial intelligence in sales provides companies with a competitive edge, enabling them to anticipate customer needs, fine-tune pricing tactics, and deliver tailored interactions, resulting in a distinctive and immersive customer journey.

AI is excellent for us in calls with customers/prospects as a meeting assistant, and one of the easiest, most high impact areas to leverage AI in your workflow. There are so many AI meeting assistant platforms out there, they more or less do the same thing: Transcribe meetings Provide summaries of calls Give live feedback With some additional work within (or outside) of these platforms, you can leverage AI to figure out where customers/prospects are getting lost during calls, what messaging is working, what they are most excited by in your solution, etc. at scale and in minutes as opposed to hours.

AI can open new ways of doing things you never did before. Updating a system from an unstructured text, deriving information to be passed to your systems, analyzing results. Learning how you can automate tasks by learning how to call APIs can be a booster to your demos and sales.

Understanding AI capabilities and limitations is essential for utilizing AI effectively. For example, Prompt engineering involves crafting queries that generate the most suitable and focusing on conversational and problem-solving abilities is more crucial. Data is another key aspect to enhance your AI literacy, consider exploring new AI tools that can help you in these areas: 1. IBM Watson Studio 2. Google Cloud AI Platform 3.Microsoft Azure Machine Learning 4.TensorFlow: An open-source machine learning platform from Google 5.PyTorch: Another popular open-source machine learning framework These tools can help you develop and implement AI solutions.

While AI automates tasks, refining strategic thinking, emotional intelligence, and relationship-building ensures enduring value. It's the blend of human expertise and technological advancements that truly sets professionals apart.

A couple of key skills to focus on: ? AI literacy: Understanding AI capabilities and limitations - plenty of free courses around from IBM, google and others to get started. ?Prompt engineering: Crafting queries to elicit the best AI responses. Although eventually this may be ok to be a good enough skill - instead focusing on conversational and problem elucidating skills. ?Data interpretation: Analyzing insights for strategic decisions using AI. ?Ethical AI use: Applying AI responsibly, considering privacy and bias is important especially in the context of propritiery information and PII.

AI has the capability to streamline repetitive and time-consuming tasks like data entry, lead nurturing, and follow-ups. This enables sales representatives to dedicate more time to cultivating relationships with potential clients, finalizing agreements, and delivering tailored services.

Always OWN any content you share as yours. This implies using AI (of any kind) as another tool in your toolbox, alongside spreadsheets, grammar correctors or CRM systems. Use AI for to help you create the content you will share if you wish, but take AI product as another input into your workflow. Curate everything and produce something that will be yours. Then you will maintain your signature in your communications. And when asked how you did it, be transparent. There should be nothing wrong in using tools.

As this is foundational to ethics: do the right thing when you are incorporating AI into your presentations/cadences/workflows, etc. Know how reliable your LLM is, try to be aware of any particular biases that might be relevant to the business case you’re dealing with. Naturally, what the AI gives as an output should INFORM, NOT MIMIC your final output. The final version needs to be yours without question. AI can be incredibly useful as an aide but one must be aware of its limitations and how that determines their own direct influence.

- The role of sales engineering can be redefined by leveraging AI to automate routine tasks, freeing up time for creative problem-solving and strategic thinking. - Encouraging yourself and other team members to learn related AI tools and experimenting can be fun which will also help in improving productivity. - No one can replace human so instead of fearing, start embracing the technology. ??

One of the most powerful ways I have used AI to help Marketing understand what prospects are most interested in our product and how we can message it better. I do this by getting call transcripts, making some edits to the transcript, and prompt Large Language Models (LLMs) like Claude to review the transcript and tell me what are things the prospects said resonated with them in our platform, what are things they asked for that aren't in our platform, what roles/teams we spoke to, etc. Using LLMs like Claude to extract this information, we are starting to come up with messaging for different people we talk to as well as figuring out how to show off parts of our product in different ways. With AI, this has taken an hour as opposed to days.

Clients want a partner(typically human) they can trust and work alongside. They want our brains and expertise to guide any solution, let alone AI systems, to the desired outcome(increase X, additional time savings, etc). In practice, this means learning about the prolific AI tools, or any tool with some buzz, in your industry & being able to give your opinion. Lean into being a Subject Matter Expert & lending your advice to the human you meet across the screen(or the table)??

To address these privacy concerns with AI: ?Anonymize sensitive data:Ensure that personally identifiable information (PII) is removed or anonymized. ?Implement access controls: Establish strict access controls to limit who can use and what information they can share with the AI, reducing the risk of unauthorized access or data exposure. ? Secure data storage: Ensure that data storage and processing systems adhere to industry best practices and security standards, reducing the likelihood of data breaches. ? Regularly review AI-generated content: Periodically review the content generated to ensure it aligns with your organization’s privacy policies and industry regulations – trust, but verify.