Prepare your data on your journey to AI
June 20, 2018
The future of big data and AI are constantly being speculated upon, but there’s no doubt that in terms of the supply chain, it will assist in more accurate decisions and improved speed to market. One of the recent studies conducted by MIT Sloan quoted ‘bad data is simply paralyzing’. This is one of the biggest issues every organisation faces – they don’t understand the data they need for AI.
We recently attended the “AI, Data and Cloud Conference” in Hong Kong, hosted by IBM to explore how organisations can plan for moving to the cloud and once cloud-based, how they can leverage the services that exist to support their AI projects and to get the most from their data. It was an action-packed event with 2 breakout sessions – ‘Fueling AI Innovation’ and ‘Make your Data Powerful for AI’ throughout the day.
Here are some of the key takeaways from various speakers:
- Dr. Evaristus Mainsah: “The Cloud for Smarter Business”
- Future of business will ride on the cloud architectures you are defining today
- Enterprise AI services existing today can support Conversation, Document Conversion, Language Translation, Retrieve and Rank, Speech to Text, Visual Recognition and many others
- Gary Chan: ‘Put your data to work with AI”
- Data monetization will become a major source of revenues according to Forbes
- AI will help power the next phase of decision making and profitability
- In 2021, AI augmentation will generate $2.9 trillion USD in business value and recover 6.2 billion hours of worker productivity, according to Gartner
- On the journey to AI, most organisations are currently between using BI and data warehousing or have deployed self-service analytics. Developing new business models is the next part of the journey
- 81% of organisations do not yet understand the data required for AI
- Other reasons why many businesses are not further along the journey to AI include disparate data types, various data sources, data silos, data quality challenges and talent shortage
- Sushil Asar: ‘How to build a future-ready virtual assistant?’
- Cognitive computing enables systems that process and act on data like humans, they understand, they reason, they interact, and they learn
- Chatbots have often failed, reasons include that they were implemented as technical POCs, they were not user focused or they were given too large a scope
- As AI and voice recognition improves, chatbots will become a primary communication channel, supplementing many human channels and offering 24×7 availability
- Key decisions in creating a virtual assistant include
- What is the purpose, for whom is the virtual assistant designed for and what will be its domain?
- What channel will we use (single or multi-channel)?
- What conversation engine/platform will be used?
- How will we manage and operate the virtual assistant application?
- When designing the chatbot dialogue, the audience and the audience intent should be kept in mind
- Consider the personas and context of the audience
- A virtual assistant must have distinctive personality, conversation experience, be a trusted advisor, be able to handover to a human and be able to continuously learn
- Owen Chen: ‘Re-imagining your industry with Blockchain’
- Blockchain will do for transactions what the Internet did for information
- $3.1 trillion USD blockchain business value will be created by 2030 according to Gartner
- Successful orchestrators, including Airbnb, Uber and Netflix, grow revenue faster with 8x market value multiplier
- Blockchain works well when there are high value assets, intermediated services, multi-party transactions or flows and unique trust requirements
Did you attend? We would love to hear your thoughts about the event and the potential future of data and AI in your business. Tweet us @adjunosolutions