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How APIs, Edge Computing and AI will Evolve in 2018

How APIs, Edge Computing and AI will Evolve in 2018

  • Laurent Bride
    When he joined Talend, Laurent brought 17 years of software experience, including management and executive roles in customer support and product development. Most recently, Laurent was CTO at Axway where he was responsible for R&D, Innovation and Product Management. He has also spent more than nine years in the Silicon Valley, working for Business Objects and then SAP. Laurent holds an engineering degree in mathematics and computer science from EISTI.
  • January 29, 2018

 

If you’ve spent any time reading the round-up of 2018 technology predictions, you’ve likely seen Artificial Intelligence (AI) highlighted in nearly every one. The reason for this is because AI has a seemingly limitless number of applications and use cases for the enterprise. In fact, according to Gartner, over 85% of customer interactions will be managed without a human by 2020. While AI is definitely a ‘hot topic to watch’ in 2018, there are also a few other tech areas that will have equally exciting momentum and just as big an impact on the enterprise in the year ahead. Following we’ll take a deeper look at what some of those will be and how they might shape 2018.

Marketplace for Artificial Intelligence Services Emerging in 2020

Although the noise surrounding AI is deafening, the art and application of this technology requires a deep mathematical understanding often only found at academic institutions or enterprise organizations like Microsoft Corp., Google and Amazon. It will take several more years before mainstream businesses can create and apply their own AI models and algorithms in real-time with any meaningful outcome.

As a result, the AI services marketplaces will begin to emerge in 2020, much like app stores, these new marketplaces will resell specialized AI services and algorithms that companies can instantly buy and implement within their business.

Although the noise surrounding AI is deafening, the art and application of this technology requires a deep mathematical understanding often only found at academic institutions or enterprise organizations like Microsoft Corp., Google and Amazon. It will take several more years before mainstream businesses can create and apply their own AI models and algorithms in real-time with any meaningful outcome.

As we pointed out in our predictions last year, AI is only as intelligent as the data behind it—putting a higher emphasis on the importance of data quality and governance. Additionally, organization overall are still not yet at a point where enough organizations can harvest their data well enough to fulfill their AI dreams. So if you don’t yet have an AI strategy for your business, you better get moving because companies that don’t have  AI embedded in their applications by 2021, will surely begin to lag behind their competition.

Enterprise, Hybrid Cloud Deployments Accelerate

In 2017, we saw an increasing number of companies shift from simply ‘kicking the tires’ on the use of cloud and big data technologies, to actually implementing full-blown enterprise deployments, with many taking a hybrid approach to cloud in particular. In 2018, more will follow suit. According to research by IDC, “Enterprise spending on cloud services and infrastructure will be more than $530 billion by 2021 and in excess of 90% of enterprises will use multiple cloud services and platforms.”

For example, take NTT Docomo, a leading Japanese telecommunications company with more than 53 million customers (as of March 2008), representing more than half of Japan’s cellular market.  . The company is building a cloud-based enterprise data lake on Amazon Web Services to improve efficiency and collaboration across its entire company portfolio. Executives across many industries are realizing they need to allow users a more efficient way to securely access data without having to request authorization from multiple systems and to implement flexible, agile infrastructures that will enable their teams to fully utilize big data analytics.

A hybrid cloud approach allows companies to obtain the cost savings of the cloud, while protecting its existing on-premises investments, intellectual property and data security.

Use of Digital Twins Inform Business Strategy

Digital representations of physical structures, or digital twins, have been used for years in complex 3D renderings. But more recent innovations in data analytics and IoT have pushed advances in 3D modeling to augment business strategies and decision-making in the enterprise. In 2018, more organizations will utilize digital twin technology to visualize and manage complex environments efficiently within a digital workspace.

In 2018, more organizations will utilize digital twin technology to visualize and manage complex environments efficiently within a digital workspace.

 

“The adoption of, and hype around, digital twins is growing,” says Roy Schulte, VP at Gartner. “Digital twins are the next step in the Internet of Things (IoT) driven world, where CIOs are increasingly leveraging IoT technologies in their digital business journey.”

EU Banking API Revolution

The European Union’s PSD2 directive is set to create new competition for banks, more options for consumers, and fundamentally new business models based on shared data.

PSD2 allows third party businesses like Amazon to access your bank account – with your permission – rather than having you go through PayPal or Visa, and it opens up APIs so new players, such as Mint.com, can consolidate your various accounts into a ‘single sign-on’ type of environment. PSD2 also brings stronger security for consumers shopping online in the EU.

PSD2 will catapult data security, data integrity and consumer trust will to the forefront, forcing APIs to become mission-critical to the banking industry. Set to take effect in January 2018, PSD2  will help the EU banking industry shift from being slow adopters to tech innovators. Obviously, any U.S. firm doing business in the EU will also need to comply with these new regulations.

Edge Computing Accelerates

From IoT, self-driving cars and the next phase of Augmented Reality (AR) wearables to go mainstream, calculating and analysis needs to happen instantaneously on devices in what’s called Edge Computing.  After all, no one will want to ride in a car that relies on cloud servers based who knows how far away for information during emergencies.

Advanced data processing and analytics capabilities are needed to ensure these steps can happen in real – time on the edge devices themselves. For example, limited compute and storage capabilities will necessitate a program to examine data quality and sort through what’s needed and what’s noise in the terabytes of information now being captured. Moving forward, more companies across all industries will look to incorporate edge computing into their strategies—for example, long-haul trucking and trucking manufacturers are already moving in this direction.

Conclusion

While each of the areas outlined above are all very exciting and have tremendous potential in terms of growth and impact on our day-to-day ways of doing business and consuming goods or services, this is just the tip of the iceberg. There are many more bleeding edge technologies that will push innovation forward for businesses this year (like Apache Beam). The question becomes: How will your business use them? 

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