Conversational artificial intelligence (AI), encompassing chatbots, voice assistants, and messaging interfaces, has enormous disruptive potential across industries. Recent advances in natural language processing (NLP) and machine learning have supercharged capabilities, while strong demand is fueling rapid market expansion.
This article analyzes 5 major predictions regarding the future of conversational AI based on trends and expert forecasts. For business leaders and technology decision makers, understanding these expectations provides valuable insights into how and where to leverage conversational AI today and tomorrow.
1. Over 20% Annual Growth Will Expand Market to $18B+
Conversational AI is currently a $6.8 billion market predicted to reach over $18 billion by 2026, reflecting massive 21.4% compound annual growth (see Figure 1). The dominant region is North America, home to most leading conversational AI vendors like IBM Watson, AWS, Microsoft, and Google that offer NLP solutions to power next-gen applications.
Figure 1: The conversational AI market has strong growth projections exceeding 20% CAGR. (Source: Market and Markets)
The COVID-19 pandemic restricting in-person activities reinforced remote capabilities like conversational AI. However, even more impactful is rising competitive pressure across most sectors forcing investments in better customer and employee experiences. Conversational AI delivers significant benefits here via 24/7 automated yet personalized engagements.
2. Messaging Becomes Hot Channel for Chatbots
Messaging apps like WhatsApp and Facebook Messenger provide a compelling new channel for conversational AI. Over half of messaging users say chatbots directly within popular platforms makes them more likely to buy goods or services.
This "conversational commerce" approach also taps rising consumer expectations of faster, more contextual engagements. As Figure 2 shows, most customers are willing to pay more for effective interactions across industries like retail, financial services, and healthcare.
Figure 2: Customers expect highly effective service and are willing to pay more for it. (Source: PwC)
With messaging apps now counting billions of users worldwide, their stickiness and existing habits present a lucrative channel for conversational AI. Companies from startups to enterprise brands are already developing commerce-focused chatbots for these platforms.
3. Digital Workers Democratize Process Automation
While customer chatbots generate headlines, arguably one of the most disruptive emerging applications of conversational AI is for automating internal business processes. Dubbed "digital workers", these tools combine intelligent process automation with natural language UIs for managing workflows.
Digital workers act as artificial employees embedded into departments like finance, HR, and IT. After training, they handle manual, repetitive tasks allowing human staff to focus on higher judgement initiatives. Colleagues interact with digital workers through workplace apps like Slack using natural language (see figure 3).
Figure 3: Natural conversation enables simple communication with digital workers. (Source: AIMultiple)
While still early days, IDC predicts enterprise spend on digital workers will grow from $500M in 2021 to nearly $14B by 2025. Their accessibility via conversational AI allows any employee to leverage robotic process automation. This democratization can mitigate rising business costs from factors like the Great Resignation.
4. Intent Recognition Becomes Key Differentiator
As conversational AI matures, capabilities for understanding context, meaning, and user intent will separate the best solutions. Already 30% of customers are willing to pay more for personalized recommendations during engagements.
Advanced NLP provides the foundation. Chatbots can now dynamically assess user needs based on complex dialogue, instead of just matching keywords and scripted responses. They then tailor interactions by validating assumptions, clarifying specifics, and adapting recommendations using decision intelligence.
For example, CEAT‘s sales chatbot asks qualifying questions to understand customer vehicle usage before suggesting the most appropriate tires. This conversational approach delivers over 20% conversion rates.
Expect intent recognition and contextual recommendations to increasingly define great conversational AI moving forward.
5. Multimodal Conversations Will Dominate
While text-based chatbots pioneered conversational AI, voice-based interfaces are catching up quickly. With over 120 million voice assistants now in the US across smart speakers and smartphones, vocal queries are becoming habitual for many consumers.
These multimodal demands lead to our final prediction – conversational AI will need to flexibly engage users across both voice and text interfaces. Some conversations may start with voice but require screen-based interactions such as selecting images or reviewing data visualizations.
Supporting diverse modalities like touch, sight and sound makes conversational AI more inclusive while fitting into more real-world usage contexts. Users want to converse however they prefer or their situation affords. Expect multimodal conversational AI to therefore become the norm, especially for areas like conversational commerce.
Recommendations for Implementation
Conversational AI has progressed from early experimentation to delivering proven value across industries. For companies exploring opportunities or struggling with early initiatives, here are best practice recommendations based on research:
- Focus on high ROI areas first like FAQs, lead generation and qualifying
- Measure capability needs – intent recognition is powerful but also more complex
- Test MVP chatbots iteratively before scaling
- Evaluate cloud vs custom development approaches
- Plan for multimodal – start with dominant modality but enable expansion
- Choose prebuilt solutions to accelerate time-to-value
With a thoughtful roadmap aligned to use cases, conversational AI can start optimizing customer and employee engagements today while offering future extensibility.
The Future is Bright for Conversational AI
This article explored 5 major predictions that will shape conversational AI advances in the coming years:
- Total market growth exceeding 20% annually
- Messaging platforms becoming a top channel
- Digital workers democratizing process automation
- Intent recognition emerging as a key differentiator
- Multimodal conversations better reflecting real-world usage
For business leaders, these trends provide actionable insights into where and how conversational AI can drive value now while innovating for tomorrow. Reach out to a vendor partner like AIMultiple to discuss your roadmap:
