With the emergence of AI filling the position of Sales Development Representatives (SDRs), the sales landscape has shifted overnight, automating and improving almost every aspect of the outreach experience. From finding leads to personalizing emails to booking meetings, AI has everything covered. But one key aspect is missing: can AI handle objections when a prospect tells the SDR no during a sales call? In this piece, we’ll explore how well AI SDRs have been performing with objection handling so far, where they fail, and why humans still need to step in.

Why Having the Ability to Handle Objections is Crucial for Sales

Objection handling is crucial for the sales process. As one progresses through a sales opportunity, objections come naturally. Once an interested party receives proper information, they’ll have questions or concerns to clarify what’s being presented and how those objections are appropriately handled can suggest whether or not the sale will close. The debate of AI SDR vs traditional SDR becomes especially relevant here, as AI may struggle with the emotional intelligence and adaptability required for complex objections. Yet the capacity to handle objections appropriately comes from critical analysis, compassion, a willingness to bend, and authenticity all things that only a human salesperson possesses.

How AI SDRs Typically Respond to Objections

AI SDRs of the present respond to objections based on predetermined responses and intelligent dialogue trees. An AI SDR trained and re-trained on thousands of sales interactions can determine what objections were common among past clients. Was it the price? Timing? Company compatibility? and either auto-populate a response to the objection or provide one without prompt. This means that AI SDRs can address objections in seconds quickly, efficiently, effectively when they know based on historical information and trends that frequent issues may arise. This helps push through various stages of conversations while decreasing back-and-forth time.

Real-World Problems: Nuance and Emotion

While many advancements have been made, AI fails at overcoming objections that involve nuance, context, or emotional understanding. Objections are not always black and white. They either reflect a bigger issue at play, concern a unique personal experience, or stem from an emotionally hesitant position. Usually, AI does not understand such nuances. But when it fails to do so and responds with an extremely generic or off-base response, it annoys the prospect and potentially ruins the buyer persona.

AI for Objection Handling Lacks Empathy

One of the most important elements in overcoming objections and properly handling them is empathy. A human salesperson can connect on a more personal and human level to showcase their understanding of a situation or concern a prospect may be facing. However, AI-based systems cannot comprehend or respond to nuanced emotional undertones; an intonation of uncertainty or routed frustration does not register because it’s coming from a non-human. Thus, when an AI-based system overlooks a slight objection based on someone’s care for an issue or frustration over something, it fails to acknowledge the situation based on the programmed response; yet, this failure comes across as callous and and even worse forces prospects to step away from the conversation, ruining rapport in the process.

AI for Objection Handling Creates Too Much Automation

Over-automation is a problem. This means that businesses do not pay attention to the nuance of what surrounds any given interaction, so an AI SDR depends upon the conversations it has had before it to know how to sound and what to say but those stuck in the weeds do so by assuming one prospect’s situation is commonplace. But it’s not. Over-automation creates ineffective objection handling because people want custom service from someone who knows beyond just the sales component directly related to the questions at hand; they need broader context, something that AI cannot provide but a human can.

Real Life Example: Price Objection

Consider the price objection. An AI SDR may respond to this type of objection with a scripted response about value or offering an automated discount. But the price objection in the real world is much more complex: it comes from a fixed budget, corporate buying rules, or competing offerings. Absent from the context, AI might respond incorrectly. But a human SDR receives this and perhaps anecdotal information to craft a much more persuasive and relevant response to the objection.

Nuanced Objections Require Human Discretion That AI Does Not Yet Have

Sophisticated objections in terms of comparing to competitors, needing to understand customization or highly technical questions require discretion that AI does not have yet. Only human SDRs can assess these situations based on learned professional experiences, and apply critical thinking and creativity, to respond accordingly. Human discretion means that in the course of a conversation, response can be modified to articulate an appropriate answer which AI cannot yet do, correctly, at this time.

Human Intervention Can Teach AI Over Time to Address Objections

While AI may fail to address objections in the short term, the long term potential with human intervention is great. If a sales team listens to an interaction where AI was involved, they can note where the AI response failed and teach it what it will take to improve its systems. With periodic human intervention, obsessive learning capabilities can adjust literally overnight to ensure that down the line, AI may respond better to more complex objections next time.

Ethics and AI to Overcome Objections

Ethics and overcoming objections involve truthfulness, integrity, and a response to customer needs and wants. For the objection prevention and handling process to be successful, it cannot come from deception or unethical means. Yet humans must actively monitor AI in this area. For example, should a company have a sordid past, AI-generated outreach one day could reference that history; if not properly vetted by a human post-process, AI could provide an erroneous answer in conversation based on what it generated previously. Humans must audit AI consistently to ensure it does not function on an unethical ethics plane, something that jeopardizes a brand’s potential to keep its image intact.

The Best Approach is a Blend of Human and AI Efforts

The ultimate solution for objection handling is a blend of human and AI efforts. AI is capable of addressing the fundamental, rote objections and it can do so quickly and efficiently, while human SDRs can address those on the more emotional side that require a more delicate touch. When companies are able to find the balance between employing AI automation where necessary but adding human touches at the proper times, they develop a superhuman type of objection handling effort that harnesses the best of systems and people for the emotionally based, pertinent responses.

Training Sales Teams to Use AI

In order to best implement artificial intelligence into objection handling with other tools, sales teams with which AI interfaces must be extensively trained. SDRs need to be aware of AI’s pros and cons as well as when it’s better to engage with AI and when it’s better to take an entirely different route. This arms SDRs not only with the ability to work in tandem with AI but also with the awareness of when their engagement would be best so that prospects are not left frustrated and confused on a call, leading to negative sales outcomes.

Continuous Evaluation and Scaling Adjustments

Determining whether AI is successful at overcoming objections should be part of a continuous evaluation process. By assessing KIPs customer satisfaction ratings, percentages of objections overcome, and other successful interaction results organizations will know if the AI-driven experience was successful or in turn, sales teams can adjust their approaches. Continuous evaluation and assessment allow for a continuous adjustment approach for organizations to best learn how to balance the use of AI versus human contribution.

Future Prospects: AI Advancements in Emotional Intelligence

Advancements in future technologies surrounding emotional reading and language processing will allow AI to increasingly overcome sales objections over time. For example, as technology gets better, AI gets better at sound understanding of emotional triggers like tone, stutters, anger, excitement, or worry within a conversation, which provides a better gauge of the emotional and situational connotation of any prospect statement. Therefore, the AI systems that control sales development representatives will be better able to generate AI responses based on a more significant emotional understanding and situational appreciation relevant to the needs and emotions of the prospect.

Moreover, future technology surrounding natural language understanding will give AI a better idea not only of what a prospect is objecting to but more about why it matters. With greater situational awareness, an AI-driven sales development representative may notice a slight change in a prospect’s concern and subsequently modify their response mid-sentence to get to a more profound issue than the prospect ever put forth. Ultimately, this will allow for a more genuine and human-like exchange between the SDR and prospect, leading to more rapport and credibility.

Yet with all this progress, human guidance and execution will always be a component for successful objection resolution. After all, humans possess qualities of empathy, intuitiveness, critical thinking and creative problem solving that even the most advanced AI options cannot replicate. Therefore, the answer is collaboration; AI and human SDRs can supplement one another’s efforts AI can instantly respond to the more basic, formulaic objections; humans SDRs can jump in anytime emotional sensitivity or situational context is required.

Ultimately, thanks to AI’s future potential, SDR teams will be better prepared to manage the intricacies of sales conversations with greater ease, empathy and success. The more AI develops, the more human factors will come into play yet not as replacements for their roles but as supportive elements for SDRs who will have more time to focus on higher-level relationship building factors. The organizations that leverage every possibility from the most advanced AI to the most thoughtful human concepts will prosper by having an advantage for naturally and successfully addressing objections for credible relationships with customers and long-term growth in sales.

Staying Ahead: The Importance of Adaptability

Yet no sustainable competitive advantage is more effective than adaptability. As cultures change in their desires, markets fluctuate and expectations rise companies are under immense pressure to evolve continually. Therefore, while implementing the AI SDR technology, for example, would increase efficiency and scalability, a data-driven approach to new sales opportunities (i.e., virtual cold calling or prospect engagement) provides better uniformity, without an adaptive process to enhance those efficiencies, the uniform advantages will be moot when stale resources don’t service customers or market changes.

This advantage not only requires internal buy-in and resources from the company but also requires ongoing efforts to determine what works and what’s needed once AI tools roll out. A company that will seek feedback about its AI-infused cold calling, for instance, to see if it’s working, whether it’s efficient, if it can be quickly adjusted and new findings embraced and accepted, is a company that respects the power of evaluation and adjustment and one that is more likely to surpass its competition for benefits. Adaptability reminds companies that nothing is ever good enough; there’s always room for improvement.

Furthermore, successful adaptability relies on AI systems collaborating with salespeople. However fast and deeply analytical AI may be in processing the sales funnel, AI will never be able to replicate the human instinct, decision-making and compassion needed to process the complexities of significant client dealings and related pushbacks, many of which will only work out in everyone’s favor with a human approach. Thus, sales teams will forever need to rely upon AI systems with proper human oversight, interruption and direction. Such measures will guarantee all outreach efforts are customized, relative to past conversations and probably have a greater emotional attachment to prospects as provided by AI data collection efforts.

Thus, those companies who successfully merge human-sale persons with AI systems who also foster an atmosphere of adaptability will always have an advantage maintaining a better relationship with their clients and learning how to overcome sales objections in a way that works best for everyone, blossoming into more profound relationships built upon trust and understanding. 

Adaptability nurtures a continuous experience for the customer by adopting a fluid response to what may be needed at the moment. When companies notice what has changed, their engagement becomes more nuanced each time, ensuring that every phone call or email has substance and usefulness. Therefore, by creating an adaptable culture, the long game can be achieved toward success within sales and beyond for sustained competitive advantage and transformed loyal customers. But this can only occur through adaptability through time with enough opportunity by partnering with Human sale agents and AI systems.