A 2022 Harvard Business Review cited survey found that 81% of respondents believed companies without AI sales (also known as intelligent algorithms) tools would be at a competitive disadvantage. However, that percentage increased to 94% among respondents who had already implemented or implemented AI solutions.
Artificial Intelligence (AI) stands out as both an opportunity and a source of challenges that customers and sales must face. Drawing a line between repeatable tasks and non-repeatable or considered admin-like is more challenging. The topic is much more complex at the tactical and operational level for every company and every product. The other day, I received a synthetic call that made me feel like I was talking to someone whose voice is used robotically. I don't want to get censored here, telling how I started to test this. Still, it answered in specific scenarios, giving me an "artificial" conversation vibe that sets me up with something like a cyberscam. The voice responded to my questions, but these were not voices from the real person. Whatever its intention was, it wasn't a great experience lacking human touch nor a great way to convince me to buy or commit to a trial.
Someone said once, "Cold calling is over." Well, in the meantime, we see that in 2024, cold calling was still the number one way to acquire new customers. Someone once said, "The PLG is a new way." 74% of companies declare that they have moved to this point, but we slowly see the problems with customer retention in this model, while many of the companies keep their sales lead growth teams working on more significant deals. While these trends are substantial and hard to ignore (and we shouldn't), we also need to understand that the rise of AI in sales or GTM functions will go through the same hurdles. I don't think synthetic voices are the way to go if you want to win customers, and that's my preference as a customer. I want to talk to humans. Before I admit that, I wanted to see how we overcame a couple of issues that I see down the journey.
Beyond synthetic voices and AI's capability to mimic human interactions, a broader spectrum of AI applications in sales requires thorough consideration. The promise of AI to augment sales processes is undeniable, yet it's essential to navigate the area with a strategic mindset, addressing potential pitfalls ahead.
Data Integrity & privacy is creating extra urgency. One of the biggest challenges in leveraging AI for sales is ensuring data integrity and protecting the privacy of many stakeholders involved. As AI systems feed on vast amounts of data to learn and make predictions, the quality of this data becomes a challenge. Misleading or inaccurate data can skew AI's output, leading to flawed or catastrophic decision-making. Moreover, with increasing regulations around data privacy (such as GDPR in Europe and CCPA in California), companies must tread carefully, ensuring their AI tools comply with all legal requirements to protect customer data. Adopting transparent data collection methods and securing customer consent will align with legal standards and build trust with your clientele. By the way, what's the standard? What if I leave the company? Can I be sure that a third-party artificial voice maker will delete my data? Is it secured? Nothing we can't overcome, but indeed, a new set of challenges many companies will need to decide about while moving to the new space.
Balancing automation with the human touch hasn't been figured out. While AI can significantly enhance efficiency in sales processes, the importance of human interaction cannot be overstated. The vast majority of humanity is considered to be a social animal. As much as we hate these out-of-the-blue cold calls, we still consider personalized customer experiences to be of considerable value, and the challenge lies in balancing automation with genuine human engagement. It might take us longer to accept and adapt to buying from the machine, but remember that you can only sell some things through a vending machine. We need to figure out where to draw the line for these interactions. In the meantime, sales teams must leverage AI to handle repetitive tasks and data analysis, freeing up time to build relationships and provide personalized advice that AI cannot replicate; rightfully, a higher degree of AI adoption in the PLG space is expected. The hybrid approach ensures that while AI optimizes the sales process, the human element remains at the core of customer interactions.
Training and adaptation are among the most underestimated parts of the sales world we are about to live in. Integrating AI into sales strategies also necessitates a focus on training and adaptation. Sales teams need to be equipped with the knowledge to utilize AI tools effectively and understand their capabilities and limitations. Sales is becoming a complex game that requires more training. The buyers are better informed, content is available for most of them, and we are still dealing with many systems that are out of sync.
On top of that, we are drawing new lines of division between SLG and PLG, Human Touch and AI-Touch, etc. This creates many expectations for any salesperson. Continuous learning and adaptation are key as AI technologies evolve. Organizations should support a culture of innovation, encouraging employees to embrace new tools and methodologies while providing the necessary training and support.
Most importantly, organizations must measure the pace and effectiveness of these changes. We need new frameworks that help us manage this without disrupting all motions that work too much, offering ongoing returns from the previously made decisions. Due to the rise of complexity in the sales process, we face a higher risk of failing to hit our targets.
Ethics & transparency. Lastly, ethical considerations and transparency in the use of AI are critical. Sales organizations must ensure that AI applications do not inadvertently introduce biases or unethical practices into sales processes. This involves carefully selecting AI tools, conducting regular audits for bias, and maintaining customer transparency about using AI in sales interactions. This will put more pressure on both environments, being intrinsic and endemic. Your product will need to be transparent about how the AI is being used, and while considering vendors, you expect them to be under a similar level of transparency. Of course, piracy will always exist, so we don't look for anything bulletproof; we look for a new standard.
Conclusions
Moving forward with AI in Sales is offering a creative set of tools on steroids called AI. These can allow you to be a solopreneur who can complete more daily tasks, get hired as a contractor for many companies, or level up any sales team in a larger company. I like to look at this like an artist (for clarity, I have ZERO artistic skills) who has a variety of painting methods, types of paints, brushes, colors, etc., to paint a beautiful landscape. We just added something that helps us to paint faster with a few strokes.
(a few considerations for all of us on how to make this work)
Don't wait. My first recommendation is to start adopting this new way. Staying behind is riskier than trying and failing. Your product, sales, marketing, and finance must know where they can use these tools and engage with the right vendors and consultants to help you adopt them. Throwing people into inefficient processes shouldn't be your first choice. The data suggest that top-performing stock companies usually have a high adoption rate for new technology. Don't need to say you have to be thoughtful and don't change your CRM each year.
Privacy measures. Get your standard in place. Don't wait for the government to give you something you will work with. Set your guidelines and principles that you want to follow. This should be one of your fundamental policies in the company that every function can follow. Since AI systems rely heavily on data to operate effectively, ensuring integrity and privacy are covered and followed. Poor data quality can lead to inaccurate AI predictions, and neglecting privacy can result in legal repercussions and loss of customer trust. Establish stringent data governance frameworks. Adhere to privacy regulations by implementing transparent data collection practices and obtaining explicit customer consent. The review process should update data practices to keep pace with evolving regulations and standards. Consider employing privacy-enhancing technologies (PETs) to minimize data exposure while maximizing utility.
It's not an either/ or question. Work with the team to determine the tactical and operational hybrid model, including AI automation with the human touch. Each of these processes should be mapped with the tools and human interaction. That should help you to determine what tools your teams need. Despite AI's ability to enhance efficiency and personalize interactions at scale, the human touch remains irreplaceable in building deep, trust-based customer relationships. Identify which interactions are critical to a human touch. There is potentially a gray area where you transition from automation to human touch, leveraging AI insights to guide human interactions, ensuring a personalized and empathetic customer experience. Remember, if there is data that the model can use to train, you should leverage that to one of these approaches.
I want you to know that sales enablement is your real concern. Investing in the function will help you to manage the murky waters of all complexities. You need someone in the organization to look across these processes, identify the skills gaps, and put them on the agenda for training purposes. The sales landscape is rapidly evolving with the introduction of AI tools, making ongoing education and adaptation essential for sales professionals to stay relevant and practical. Create a culture of continuous learning within your organization, leveraging AI tools and technologies. Tools like this will shorten the time between junior rep advancement and senior rep and likely result in a faster ROI/ ramping period. Encouraging experimentation and feedback will help tailor training and support to the specific needs of your sales team or individuals.
I'm big on ethics, so I prioritize customer transparency considerations foundational to maintaining trust and ensuring the responsible use of AI in sales. Making this clear to your prospects about what you are using and how you are leveraging data is not a sign of weakness but a solid commitment to what matters in any good relationship, business or not. Conduct regular ethical audits of AI tools to identify and mitigate biases. If you can afford an external partner to do that, it would be a good practice that many of your customers would appreciate. Yes, you might not get more customers because of that, but you will also lose a few. Be transparent with customers about how AI is used in sales processes, including data collection and analysis practices. Choose AI partners and vendors who uphold similar ethical standards and transparency commitments and incorporate ethical considerations into your AI strategy from the ground up.
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