| |July 20199behalf of the action owners (using a rational agent). Why now?Several factors have contributed to this rapid growth. The pace of in-novation in conversational platforms is high and the market is fragment-ed with a large number of startups as well as big players such as Ama-zon, Google and Microsoft. Hybrid cloud is mainstream in enterprises now with corporate IT and Infosec teams building integrated services that leverage third party clouds. API and XaaS architectures have enabled provisioning of on-demand services leveraging Amazon Lexor Google Dialogflow. Lastly, the network - high speed bandwidth from 4G to dark fibre, has made access to online services cheap and seamless for both enterprises and consumers.Where do we go from here?Building a basic working prototype is relatively easy, but getting a solution to work at scale and put it in produc-tion is hard. The core of an effective conversational platform is an NLP engine that can interpret the nuances of various languages or cultures and apply AI to overcome ambiguity. A good NLP engine needs to leverage large datasets-webscale providers such as Google or Amazon have an edge here due to their access to data and capabilities which few can match. We can expect these proprietary en-gines to be refined continually and be offered as a cloud service for other companies to build on.Some Learnings:The future of conversational plat-forms is very promising and the use cases are numerous. As with any ma-jor transition in IT, the road to this future is riddled with a few potholes. First, the capabilities of the in-house team that integrates and provides these services. In a fast changing tech-nology world, finding and retaining the already scarce talent with current skillsets is not easy. To mitigate this, partnership with a specialised vendor can help. Second, user behaviour can be unpredictable and may adversely impact adoption. Ease of use, qual-ity data and enterprise scale are all vital keys to drive adoption. Even so, a shift from traditional habits that we are accustomed to requires con-siderable change management ­ for example, will the sales force adapt voice technologies or just ignore it? Lastly, the path from an innovation project to production scale will have many unpredictable twists and turns. Any transformational effort, includ-ing those of conversational platforms requires patience ­ plenty of it. Building a basic working prototype is relatively easy, but getting a solution to work at scale and put it in production is hard
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