As technology and marketing leaders are preparing for 2023, questions will arise regarding which technology advancements should be monitored and planned for. Earlier this fall, I attended Forrester’s Technology & Innovation event where emerging technology trends were discussed at length. These included:
- Explainable AI
- Edge Intelligence
- Natural Language Processing
- Extended Reality
- Intelligent Agents
- Zero Trust Edge
- Privacy-Preserving Technologies
- Cloud-Native Computing
While Web3 is likely the most discussed and anticipated emerging technology among those listed, advancing intelligent agents and natural processing language will also have a profound customer experience (CX) impact by enhancing the complexity that conversational artificial intelligence (AI) is capable of. Simultanously, privacy-preserving technologies will continue to emerge to ensure that our continuously increasing interaction with technology does not put sensitive consumer data privacy and security at risk. Let’s take a quick look at four of emerging technologies discussed at the event that should be monitored in the new year:
Web3 in reality is the accumulation of several different technological advancements that are predicted to drive the next iteration of the internet and enable openness, decentralization, and user-centricity. One of the most exciting applications is tokenization. Non-fungible tokens (NFTs) facilitate the purchase experience of digital items by enabling the ability to authenticate ownership. For brands, this could enable entirely new product offerings. One could imagine that in the the coming years, brands will be revolutionalizing CX by marketing and selling digitalized versions of their product.
Privacy-perserving technologies (PPT) advance the ability for brands to use customer data securely. Consumers are growing increasingly concerned about privacy and data security, especially in cases where sensitive customer data is collected including personally identifiable information (PII) such as geolocation, biometric, and medical history data. PPT seeks to alleviate privacy concerns by enabling more control over the usage of customer data.
Forrester provides three examples of PPT use cases:
1. Privacy filtering for viewing or accessing personal data
2. Security controls for data processing and use
3. Controls to secure the environment where data processing happens
Intelligent agents (IAs) analyze user input to autonomously perform tasks and make decisions. IAs adapt over time and are capabible of learning from previous experiences. This technology will work in conjunction with natural language processing in order to interpret user input and drive accurate decision making capabiliites. In practical terms, IAs will open the door to the next iteration of conversational marketing by advancing the capability to infer customer intent to drive next best actions.
Natural Language Processing
Natural language processing (NLP) is a broad term that encompasses many technologies. Certain NLP technologies have existed in the market for years and cannot be considered an emerging tool, per say. During the event, Forrester provided examples of emerging technologies under the NLP umbrella such as large language model. Large language model (LLM) is a machine learning model that supports a wide array of CX use cases. LLM advances the ability to generate complex chat responses. Prompt engineering drives LLM, enabling complex responses to remain as human as possible, helping to foster better chatbot conversations for customers and prospects.
While the business applications of these emerging technologies are an exciting prospect, Forrester predicts that it may take years for many of them to be readily available as commercial offerings. Adoption of these technologies will ultimately vary based on the technological maturity of the organization in question. We’re looking forward to seeing how these technologies are adopted across industries, and how they help spark innovations yet to come.
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