International Business Machines Corporation (IBM - Free Report) recently updated Watson Studio with AutoAI capabilities.
As the name suggests, AutoAI enables enterprises to automate complex arduous processes, comprising optimizing, designing and other related tasks by leveraging robust AI capabilities.
Markedly, innovation in machine learning (ML) and improvement in data set quality drives development of AI tools. IBM rolled out AutoAI with an aim to free up time for data engineers to design sturdy ML models to expedite AI deployment.
AutoAI capabilities function in sync with Watson Machine Learning to accelerate AI processes considerably. AutoAI is available in “Watson Studio on the IBM Cloud.”
IBM is leaving no stone unturned to strategically infuse AI capabilities across its offerings, which hold promise. AutoAI is anticipated to boost adoption of IBM Watson Studio services, consequently bolstering the company’s top line in the days ahead.
With AutoAI, data scientists can utilize “hyperparameter optimization capabilities” which facilitates development of AI models. Moreover, AutoAI is loaded with robust enterprise data science models, including gradient boosted trees which allow users to upscale ML deployment processes.
In a bid to empower users with deep learning (DL) capabilities, AutoAI allows access to IBM Neural Networks Synthesis (NeuNetS). Notably, NeuNetS utilizes AI to aid development of DL model and automates data synthesis across custom-designed neural networks. Further, NeuNetS provides users with the flexibility to prioritize accuracy or speed of the data model.
Increasing Spend on AI Favors Growth Prospects
Huge volume of data is being generated through a wide range of sources. In a bid to harness this data constructively, the companies intend to leverage AI to provide specific solutions and enhance solutions’ capabilities. However, deployment of AI tools is not trouble free.
For instance, per an IBM study, Shifting Toward Enterprise-Grade AI, conducted last year, 63% of surveyed individuals cited “lack of proper technical skills was a prime challenge to AI implementations.”
Moreover, according to a Forrester study, 60% of surveyed candidates claimed management of data quality to be one of the headwinds in delivering AI applications.
Markedly, IBM’s new Watson AutoAI capabilities provide companies with robust data models, consequently accelerating their AI processes.
We must note that the number of companies utilizing enterprise AI is increasing, which favors the prospects of AutoAI tool in Watson Studio. Per a report by IBM, customer satisfaction is the primary reason behind around 77% of organizations focusing on AI investments.
Further, IDC data projects worldwide spending on AI systems to hit $79.2 billion by 2022 at a CAGR of 38% from 2018 to 2022.
The move is expected to strengthen the company’s position in machine learning as a service (MLaaS) market, which is envisioned to hit $8.31 billion by 2023 per a MarketReportsWorld report, as revealed by MarketWatch.
The aforementioned secular trends reinforce IBM’s growth prospects in the longer haul.
Competition a Woe
Rising competition from Amazon Web Services (AWS) and Microsoft Azure, which dominate the cloud infrastructure services market, is a headwind. Notably, the cloud players are strengthening their IT infrastructure with advanced ML capabilities. For instance, Microsoft recently rolled out additional functionalities to Azure Machine Learning.
According to latest first quarter data from Synergy Research, IBM Cloud is classified as “strong niche player” with comparatively “lower growth rates.”
Zacks Rank & Key Picks
IBM carries a Zacks Rank #3 (Hold).
Some better-ranked stocks worth considering in the broader sector are eGain Corporation (EGAN - Free Report) , Rosetta Stone Inc. (RST - Free Report) and j2 Global, Inc. (JCOM - Free Report) , each sporting Zacks Rank #1 (Strong Buy). You can see the complete list of today’s Zacks #1 Rank stocks here.
Long-term earnings growth rate for eGain, Rosetta Stone and j2 Global is pegged at 30%, 12.5% and 8%, respectively.
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