A new study from Spitch, “Spitch Expert Survey Agentic AI,” shows agentic AI moving rapidly from proof-of-concept to practical advantages in customer contact. Based on responses from 100 executives in Germany (70% with in-house contact centers, 30% outsourced), the research highlights strong momentum, clear business benefits, and a candid view of the implementation challenges leaders must manage.

What leaders mean by agentic AI

Respondents define agentic AI as a new generation of AI systems that can break down complex requests, work step by step toward a goal, and deliver accurate outcomes – think voice-based dialogue systems that handle multifaceted queries with natural, human-like conversation.

Momentum and market outlook 

• 68% see agentic AI as a megatrend in contact centers.
• 77% believe it will massively change how AI is used in customer communication.
• 47% expect it to become the long-term standard; another 52% say that’s at least partially likely.

Why it matters: top benefits for CX, operations, and cost

• Elastic capacity when it counts: 64% rate flexible scalability during spikes as the most important benefit (another 30% say it’s important). Immediate scaling in unforeseen situations is crucial for 59% (for 32% – important).
• Always-on service without adding headcount: Half highly value 24/7 availability; 45% find it at least relevant.
• Faster answers, faster routing: 45% cite immediate responsiveness as a main advantage (another 55% see it as a key factor).
• Consistent quality and multilingual reach: 39% call consistent service quality very important (32% – important). 47% value multilingual service without translation overhead (37% – find it important).
• Data-driven optimization: Automated analysis is an important advantage for 41% and a very important one for 50%. 83% say richer data improves understanding of needs and drives better strategic decisions; 84% praise more efficient quality and process management.
• Personalization at scale: 55% rate individualized communication based on existing data as important; 36% – as very important.
• Cost-quality balance: 38% see significant cost savings with equal or better service as very important (33% important). 81% are convinced agentic AI reduces costs; 45% expect noticeable OPEX decreases. 60% firmly attribute savings to scalable AI capacity at consistently high quality (22% see it as one of the drivers).

Impact on people: relief, onboarding, and retention

Agentic AI is not just about handling volume – it’s reshaping work:

• Workload relief: Important for 50% of leaders; very important for 41%.
• Faster ramp-up: 82% believe AI-supported training accelerates onboarding; 74% say new employees integrate into workflows faster. Leaders also note onboarding is just one of many use cases (78%).
• Engagement and retention: 72% say agentic AI boosts agent motivation and loyalty by letting people focus on higher-value tasks. 

Customer verdict: faster, more consistent, more precise

From the customer perspective, the benefits are clear:

• 91% highlight no waiting time and fast answers.
• 71% appreciate being quickly routed to the right human when needed.
• 73% are satisfied with consistent quality around the clock.
• 77% welcome access to more expertise during the interaction, leading to more precise and comprehensive answers.
• 65% praise the reliability of responses.

Business outcomes: differentiation and competitiveness

• 73% view agentic-AI-enabled service improvements as a key competitive differentiator.
• 63% link agentic AI to higher customer satisfaction and loyalty.
• 69% expect a sustained competitive boost, and 73% believe the market recognizes the innovation signal.
• 81% of respondents are certain that Agentic AI leads to cost reductions.

What to do now: a practical playbook

• Exploratory phase: Use speech analytics to map key intents, refine labeling, identify clear-cut automation scenarios, and get your data house in order.
• Start with high-impact, data-backed use cases: first-line voice self-service with precise intent recognition and call steering, multilingual FAQs, password resets, order status, and appointment changes.
• Design for escalation: Ensure seamless, context-rich handoff to human agents with transcripts and next-best actions.
• Build governance and trust: Establish privacy and security controls; define quality KPIs, monitoring, and guardrails for error handling.
• Invest in enablement: Use AI-driven training and workflows to speed onboarding and augment agents in real time.
• Measure outcomes: Track CSAT, FCR, AHT, containment, resolution accuracy, and cost-to-serve – and iterate fast.