As AI continues to evolve and weave its way through more industries, the demand for access to structured, accurate data has never been greater. If you’re a business or startup positioned within the AI industry, getting hold of the data you need to provide to clients is a never-ending uphill battle, especially if the projects are coming in faster than you can scale your workforce.
Crowdsourcing skilled talent is the quickest solution if you’re an AI service provider looking to take your workforce from 0 to 100 to maximize your output.
Through crowdsourcing, you can:
- Obtain data and information without the long lead times required to source capable employees.
- Ensure you’re not sacrificing quality for output.
- Scale according to your operations and task size.
It’s clear that crowdsourcing is the gold standard solution for speedy, efficient data processing, however, it also brings its share of potential limitations and roadblocks.
Dive into some of these challenges you might face when crowdsourcing, and discover some alternative solutions to overcome these hurdles.
WHAT ARE THE TOP 3 CROWDSOURCING CONUNDRUMS THAT AI COMPANIES FACE?
1. COMPETENCY AND CONSISTENCY
In the world of crowdsourcing, it can be tricky to separate the wheat from the chaff. There are countless data annotators, transcribers, analysts, and so on who claim to be able to do the job, but can you really count on them? Finding skilled workers genuinely capable of providing the quality of work you require according to your deadlines can be a headache-inducing task.
Usually the vetting process consists of a test that the candidate has to pass to demonstrate their skills and abilities. However, simply passing the test is not a guarantee that the candidate will consistently produce high-quality work, as each crowdsourced candidate may have a different educational background and experience level.
Crowdsourcing has enabled businesses in AI and other industries to easily source and connect with talented workers, but ensuring that you’re getting quality along with convenience is not as easy.
2. RELIABILITY
Making sure that crowdsourced workers deliver on their promises is another common challenge.
Crowdsourcing offers AI companies no promise of reliability due to its unstructured nature. Individual workers are not contracted, they are hired to complete the job by a certain due date, but they can leave whenever they choose to. This means you essentially can’t guarantee delivery to your clients when crowdsourcing.
A crowdsourced worker may decide they don’t want to continue working on a project and quit halfway through. Companies then try to prevent this from happening by increasing their rates for completing the task, which cuts into their profit margins.
The lack of guaranteed reliability offered by crowdsourcing can become costly quickly and difficult to manage, especially if you have important clients relying on you to deliver their data.
3. INSTANT SCALABILITY
Another limitation of crowdsourcing is being able to scale your team immediately if necessary. If a surge of work comes in that’s beyond your crowdsourced team’s capacity, you’ll be faced with the unpleasant dilemma of either rushing to source and vet additional workers to expand your team or be forced to turn away the incoming work.
Companies who crowdsource will need to spend valuable time vetting, training and upskilling crowdsourced workers to ensure they’re up to the task. If not, it’s back to square one and they have to begin the crowdsourcing process all over again.
HOW CAN COMPANIES OVERCOME THESE HURDLES?
Although crowdsourcing presents these various challenges, it’s also the source of solutions. The most practical and time-savvy workforce solution is to outsource your crowdsourcing to a company that specializes in providing talented, vetted professionals, ready to take on your task requirements at a moment’s notice.
For instance, Werkit’s digital ecosystem provides AI companies with instant access to an array of skilled workers with data management and processing expertise in computer vision, NLU, fintech, and healthcare among other areas. Our sourced talent is extensively screened and tested to ensure we’re bringing the best and brightest workers onto our teams.
Werkit provides multiple workforce solutions, according to your task’s requirements, deadline, and size. Managed Crowds have the skills and means to take larger tasks and projects from conception to completion.
In addition to sourcing and building a custom crowd of 100 or more specialized workers solely dedicated to your project, Werkit can also tailor management solutions and train or upskill workers where necessary should you need it.
WHAT ARE THE BENEFITS OF A MANAGED CROWD?
RELIABILITY
With Managed Crowds, the expectations for performance, deliverables, and commitment are set before the project begins. Werkit holds all Managed Crowd workers to set agreements that ensure consistent competency and that projects are completed within allocated time frames.
SCALABILITY
Managed Teams at Werkit provide access to a large pool of vetted and verified talent. All Managed Team members are professionally qualified in any and all annotation tasks required, from NLP to Computer Vision.
REDUCED OPERATIONAL COST
The quality and reliability of the workforce that Managed Teams offer means that your churn rate will shrink and your operational costs will reduce. At the same time, you won’t need to increase your rates for tasks and projects to keep up with increasing overheads, allowing you to stay agile and competitive.
For an in-depth examination at how Werkit’s Managed Teams enabled transcribing and captioning ‘unicorn’ Verbit to do exactly this, take a look at our detailed case study.
No matter the task, Werkit has the workforce. If you’d like to find out more about how Werkit can help deliver the results you need for your business, book a consultation with us.