Tuesday, November 14, 2017

Forrester Predicts That AI-enabled Automation Will Eliminate 9% of US Jobs In 2018

 
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A new Forrester Research report, Predictions 2018: Automation Alters The Global Workforce, outlines 10 predictions about the impact of AI and automation on jobs, work processes and tasks, business success and failure, and software development, cybersecurity, and regulatory compliance.
We will see a surge in white-collar automation, half a million new digital workers (bots) in the US, and a shift from manual to automated IT and data management. “Companies that master automation will dominate their industries,” Forrester says. Here’s my summary of what Forrester predicts will be the impact of automation in 2018:
Automation will eliminate 9% of US jobs but will create 2% more.
In 2018, 9% of US jobs will be lost to automation, partly offset by a 2% growth in jobs supporting the “automation economy.” Specifically impacted will be back-office and administrative, sales, and call center employees. A wide range of technologies, from robotic process automation and AI to customer self-service and physical robots will impact hiring and staffing strategies as well as create a need for new skills.
A political automation backlash will briefly impede progress—and lose.
The hot-button political issue of automation will accelerate in 2018 as workers realize nearly all jobs will be affected. Automation will win regardless—because its economic value outweighs any political resistance. Forrester recommends investing in change management internally and PR externally.
Robotic Process Automation (RPA) will add 500,000 US “digital workers.”
In 2018, RPA-based digital workers (i.e., bots) will replace and/or augment 311,000 office and administrative positions and 260,000 sales and related positions. As a result, the RPA software market will exceed $500 million by the end of 2017 and double to $1.06 billion by the end of 2018.
Digital Transformation spending will emphasize automation.
2018 will recast automation as a prime enabler of the customer experience, one that uses voice and chat interaction and is backed by AI building blocks that follow conversation and intent, make decisions, resolve exceptions, complete transactions, and remove simple, standardized tasks from human work. Enterprises will invest in broad automation efforts such as automation centers of excellence that span business units.
Bots + RPA smart search + collaboration tools = faster ops decisions.
AI building blocks can create chatbots or an RPA-enabled smart search that completes the tasks faster than presenting data across case stages or redesigning the process with all its attendant integration. A bot can act as a personal assistant, centralizing information and automating personal administrative tasks. Enterprises gain productivity benefits when their employees access data from a (trusted) centralized information source.
Mainstream enterprises will deploy vital workloads on infrastructure-as-code.
In 2018, a strong inflection in software-defined infrastructure of many sorts will fuel a fervent community adopting infrastructure-as-code philosophies and practices.
More than half of ops teams will embrace continuous deployment.
The change velocity of many organizations is accelerating as they transition from half-yearly releases to monthly, primarily driven by 65% of organizations releasing applications monthly or faster. Many large organizations have already invested in continuous delivery release automation (CDRA) to drive the deployment of applications within production environments.
Testers will seize on bots to take the lead in systems development life cycle (SDLC) automation.
The recent AI and machine learning enthusiasm will accelerate in 2018. The race to further replace manual and repetitive tasks along the SDLC with bots will speed up developer work through automation. In 2018, more use cases of how to use AI and machine learning to further automate the software development testing and delivery cycle will flourish. Forrester recommends aligning software development processes around bots.
A true combined security and ops automation platform will roll out.
It has become impossible, says Forrester, to manage security and compliance initiatives manually. In 2018, security startups will eclipse many traditional network and security vendors. They will offer simplified security solutions that allow teams to create microcores and microperimeters (MCAPs) around assets in private cloud and public cloud, as well as IoT.
Your next entry-level compliance staffer will be a robot.
Banks around the globe have seen their spending on regulatory compliance grow from 15% to 25% annually from 2012 to 2016. Banks and other financial services firms typically throw people at compliance challenges—and many still manage reporting and data gathering in Excel. 2018 will see a freeze on compliance spending, as businesses begin to use automation and AI tools to cope with the increasing regulatory burden. For many banks, this will be a slow and steady burn that focuses first on new compliance requirements. For many finance and insurance firms, compliance spending will plateau before broader automation initiatives start to cut the cost of remaining compliant in 2019 and beyond. Enterprises in the financial services industry will need to convince regulators that machine learning and analysis can match human learning.

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