Greater transparency and digital transformation, what 2018 holds for artificial intelligence

Artificial intelligence

One of the most interesting trends we've seen in 2017 is the spread of artificial intelligence into areas like marketing and security.

Is this set to continue into next year, and are there new fields where AI is set to make a significant impact? Here are the views of some industry experts.

AI isn't yet ready to go mainstream, but more businesses will be laying the ground work to use it in future, says Couchbase SVP of engineering and CTO Ravi Mayuram. "Today AI is more of a trendy buzzword than practical reality, and it’s difficult to execute because AI is only as good as its data. While data integrity still varies within the enterprise, true implementation of AI is still a concept that will not come to fruition for a few years. However, we've seen early stages of machine learning applications in verticals such as advertising and retail. In the years ahead, we’ll see more industries, including industrial IoT, digital health and digital finance, begin taking advantage of machine learning within applications to provide more meaningful user experiences. Throughout this transformation, the database will play an instrumental role by accommodating rapidly-changing data at scale while keeping big data sets reliable and secure."

Roman Stanek, CEO of GoodData believes digital transformation projects will drive AI adoption, as will new legislation like GDPR. "With the massive rise of digital transformation, businesses are simply not operating how they were 10 years ago. We are collecting more data, which we not only need to keep safe, but leverage for competitive advantage quickly. GDPR and digital transformation are two facets of the same coin; digital efforts will drive the growth of your data and needs to be better protected. The business driver is customer experience and there’s no better way to improve customer experience than through AI. Robotic advisors, chatbots, active notifications and production recommendations are all examples of how AI has improved the customer experience."

This is echoed by Matei Zaharia, chief technologist at Databricks. "AI will find more business use cases, starting with verticals. Generic machine learning platforms are difficult for organizations to use, but vertical-specific solutions to common business problems will start to incorporate the newest ML techniques and transform the standard business processes."

We saw in our security predictions that some experts expect to see an AI arms race develop. But AI, along with blockchain and 5G will have an impact on combating piracy, thinks Doug Lowther, CEO of Irdeto. "This coming year will see content owners and rights holders push themselves even harder to battle piracy, with the emergence of AI. Meanwhile blockchain and the advent of 5G have the potential for both positive and negative impacts on the media and entertainment industry. There is potential for pirates to exploit blockchain to accelerate content redistribution, but there are also opportunities in blockchain for content owners and rights holders, particularly around the characteristics of cryptocurrency, immutability, tracking of ownership and smart contracts. Meanwhile the increased data connectivity allowed by 5G will accelerate OTT uptake, but could also make it easier for the distribution and consumption of pirate content."

Thorsten Trapp, CTO and co-founder of tyntec thinks enterprises will find ways to fill the gaps in AI's ability rather than waiting for the technology to catch up. "Once initial human-like interaction has been established, deeper engagement and business transactions will be handled by micro/instant apps, using more transaction-efficient interfaces. Natural language processing through AI is not optimized for the collection of structured data, such as signatures or filling out forms or credit card information. Companies won’t wait for AI to perfect this but will integrate solutions that help with the seamless hand off between natural AI conversations and the use of micro/instant apps, delivered in the messaging channel with no friction, to collect more complex data."

The process of machine learning needs to be made more transparent too says Talend CMO Ashley Stirrup. "We need to make the data and machine learning's ‘thinking’ transparent. Companies will emerge that are dedicated to the monitoring of machine learning processes. In the future, machine learning will be used to make decisions directly affecting consumers and it will be imperative that the decision-making process is highly predictive and reviewable."

Finally, 2018 will see some of the hype surrounding AI begin to die down as the technology itself improves, thinks Chad Meley vice president of marketing at Teradata. "While the hype dies down, AI infrastructure improves dramatically. There will be a 'backlash' on 'AI Hype' in 2018, and a more balanced approach of deep learning and shallow learning application to business opportunities will emerge. At the same time, investments will continue. A survey of 260 large enterprises in 2017 identified a 'lack of IT infrastructure,' surpassing all other headwinds such as little or no access to talent, lack of budget, and weak or unknown business cases as a significant barrier to realizing benefits from AI. Companies will respond in 2018 with enterprise grade AI product and supporting offerings that overcome the growing pains associated with AI adoption."

Are we on the verge of AI becoming mainstream, or does it have some way to go? Let us know in the comments.

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