Identifying key trends in Enterprise Technology for 2019

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Data Analytics
It’s becoming clear that decision-making platforms built on ‘data lakes’ are no longer enough to generate real business value. Enterprises need to embrace data value that covers the entire analytics value chain, from data and insights to people and the company’s processes. Data governance will need to be integrated with overall business strategy and aligned to a data-driven business model. In the near future, Machine Learning (e.g. self-service data platforms) and Natural Language Processing (conversational analytics) will accelerate data-driven decision making.

Artificial Intelligence (AI)
Machine Learning is already a key part of enterprise automation roadmaps. More democratic AI is on the horizon, spurred by an increase in Machine Learning solutions, rising demand for data science talent and more complex algorithms. Large platforms like Amazon and Google will prove instrumental in the explosion of ML models. 2019 is highlighting natural language programming, text analytics and strides ahead in voice search, along with more deep learning. Enterprises are already looking past chatbots and incorporating Natural Language Processing in every aspect of customer experience, while evaluating explainable algorithms.

Human-Machine Interaction
While Human Machine Interaction technologies including augmented reality (AR), virtual reality (VR) and chatbots are yet to find mainstream adoption, they are gaining traction in the enterprise. Adoption barriers will further dissolve with advances in software engines, AR/VR devices, and democratisation of content creation. Smartphones are an excellent platform for AR applications and can create a customer outreach strategy. Enterprises can also ramp up productivity with AR/VR applications to assist human resources employed in diagnostics and repairs. Also, using safe, cost-effective AR/VR applications to simulate physical world scenarios (“Twinning”) can give an edge over competitors, especially during training and demonstrations.

Internet of Things (IoT)
Security remains the main area in IoT deployments. Edge Computing will be the new focus, while blockchain and newer network connectivity standards will impact IoT over the long term. Security will improve as the industry learns from more complex deployments, with remote upgrades for IoT devices becoming indispensable, and compliance with GDPR becoming non-negotiable.

Identity, Access & Security
In highly fluid enterprise networks, the best approach is ‘never trust, always verify’. In the near future, automation and managed security services will gain wide acceptance, while decentralized identities will set the stage for a collaborative ecosystem. Enterprises need to focus on omni-channel security, backed by machine-intelligence monitoring tools and an automated framework. To leverage users’ data in business analysis and transactions, ensure user consent first, because the advent of the GDPR framework has thrown identity and security issues into sharp focus.