Home > Blog > Artificial Intelligence and Machine Learning Jobs Outsourcing: Ultimate Guide to Nearshoring AI and ML Solutions
Artificial Intelligence and Machine Learning Jobs Outsourcing: Ultimate Guide to Nearshoring AI and ML Solutions
Published: August 23, 2023
The era of artificial intelligence (AI) has dawned upon us, bringing the potential for transformative change. While skepticism inevitably lingers, visionary business leaders recognize AI’s immense potential to revolutionize operations, enhance decision-making, and drive growth.
Are you looking to leverage this multi-billion-dollar technology to your advantage? Let’s explore why businesses should stop resisting change and embrace the AI revolution through outsourcing.
AI Growth Worldwide in Numbers
The AI market is poised to reach a staggering market value of $407 billion by 2027. And it’s only expected to go up from there, with a projected annual growth rate of 36.2%.
The adoption rate of the technology is also remarkable, as exemplified by ChatGPT’s ability to amass a record-breaking one hundred million users just two months after its launch. Forecasts also show that 10% of vehicles are predicted to be driverless by 2030, given that the global self-driving car market is expected to rise from 20.3 million in 2021 to 62.4 million.
A vast majority (64%) of businesses believe that artificial intelligence will play a pivotal role in elevating overall productivity, highlighting their growing confidence in AI’s potential to revolutionize business operations. Meanwhile, despite growing fears about its impact on the workforce, the World Economic Forum revealed that the AI revolution could potentially create 97 million new job opportunities.
How will this impact the future of business amid a labor shortage? Let’s find out.
ML and AI Outsourcing Solutions in a Nutshell
From revolutionizing industries to enhancing customer experiences, AI’s impact is undeniable. One of the avenues through which organizations are harnessing its potential is AI outsourcing services – a strategic approach to boost your capacity and expertise without the need for costly in-house development.
Let’s delve deep into outsourcing and discover how it’s reshaping businesses and accelerating innovation.
Data Entry, Labeling, and Annotation
Data is undeniably the fuel that powers innovation in the ever-evolving landscape of AI and machine learning (ML). And while there is a critical need for relevant, accurately labeled data in building robust AI/ML models, studies show that nearly 90% of organizational data is unstructured.
AI cannot learn with unstructured, unlabelled data.
Clean, quality data is the cornerstone of successful AI models, as these systems learn patterns and make predictions based on the information they’re provided. As such, the foundation of your success lies not just in the algorithms but in the precision with which the data is aggregated, tagged, and identified – and that’s the essence of data annotation.
Unfortunately, the complexity of organizing can be overwhelming, especially for projects with massive datasets or intricate annotation guidelines. The solution is data entry outsourcing. By entrusting data entry tasks to specialized professionals or external partners, businesses can ensure the accuracy and organization of comprehensive datasets.
A prompt is basically a command that triggers the algorithm of an AI system. Think of it as giving an order to a computer, but it’s a bit more nuanced than that – since wrongly input data could easily result in a wrong output.
Given that, prompt engineering is the delicate art of deciphering the inner workings of AI systems. Prompt engineers skillfully coax AI language models into generating desired outputs, playing a pivotal role in fine-tuning models for specific tasks. This process involves employing carefully constructed prompts — infused with precise verbs, vocabulary, and context — to push large language models (LLMs) to their limits.
While AI’s behavior can sometimes seem enigmatic, prompt engineers rise to the challenge, delving into the intricate mechanics of generative AI, unveiling hidden errors, untapped potential, and novel issues. Their job descriptions may vary for different organizations. Still, ultimately, they share a goal: to enhance machine-generated outputs in a reproducible way and align with human intent.
With their unique ability to bridge the gap between raw AI capabilities and tailored functionality, prompt engineers are highly sought after. Sadly, the talent pipeline cannot keep pace with demand.
How can businesses planning on their AI journey navigate the skills shortage? Through outsourcing, of course.
With the help of specialized experts who understand the intricacies of prompts and AI responses, businesses can refine their AI models for more accuracy and enhanced user experience.
The success and popularity of Python as a programming language can be attributed to three key factors: ease of use, versatility, and strong community.
It boasts a rich repository of pre-built libraries tailored to implement various ML and Deep Learning algorithms. The beauty lies in Python’s simplicity – developers can rapidly run algorithms on datasets by installing and loading the necessary packages with a single command.
As a general-purpose programming language, it can also be used for various applications, including web development, data analysis, scientific computing, AI, ML, automation, and more.
When navigating coding errors or seeking assistance, developers find solace in the wealth of support. Multiple online communities, groups, and forums foster an environment of shared learning and problem-solving.
Harnessing Python’s many attributes through programming and development outsourcing can set businesses on a trajectory of success, empowering them to navigate the complexities of AI development while focusing on core strategic objectives.
Machine Learning Engineer
What is machine learning?
Machine learning works by training algorithms on data to learn patterns and make predictions or decisions without explicit programming. This involves data collection, preprocessing, feature selection, model training, validation, and testing.
ML engineers are responsible for implementing and deploying an effective machine learning model into real-world applications in this scenario. They work on transforming the research and prototypes developed by ML researchers into practical, functional systems that end-users can use.
As businesses strive to leverage ML for competitive advantage, the demand for skilled ML engineers continues to surge. To keep pace, increasingly, more companies are turning to outsourcing.
Hiring and training in-house ML engineers can be resource-intensive in terms of time and finances. Outsourcing offers a more cost-effective alternative. You can leverage the expertise of seasoned professionals without the burden of onboarding, training, and maintaining an in-house team.
With outsourced expertise, the learning curve associated with ML development is substantially reduced, translating to a quicker realization of value from your AI projects.
The cost-efficiency, flexibility, and rapid deployment offered by BPOs ensure that your organization remains at the forefront of this transformative wave.
Artificial Intelligence Architect
As businesses race to harness the AI’s potential for innovation and growth, the role of AI architects comes into sharp focus. These professionals sculpt the blueprint that underpins every successful AI endeavor.
AI architects are responsible for designing the holistic framework for AI systems, encompassing the meticulous selection of algorithms, technologies, and frameworks that will power the AI ecosystem. From enhancing customer experience to optimizing operations, their decisions resonate throughout the organization, propelling it toward AI-powered success.
Thanks to the increased digitization of businesses, the once-novel concept of outsourcing architects is now proving to be a strategic imperative for those that want to tap into AI’s potential.
Staying abreast of the latest trends, outsourced AI architects can customize your AI system to suit your unique needs and ensure that it is seamlessly integrated into your existing infrastructure and workflows.
Combined with outsourcing’s scalability, efficiency, and customization strength, their expertise positions BPOs as strategic allies in your journey toward success in an AI-driven world.
With a projected growth of 36% from 2021 to 2031, the Bureau of Labor Statistics identified data scientists as one of the fastest-growing occupations in the U.S.
Their expertise in data analysis, ML, and statistical modeling is the driving force behind everything from customer analytics to predictive maintenance. However, since hiring in-house data science teams is a formidable challenge in the post-pandemic era, forward-thinking businesses have turned to another strategic option: data science outsourcing.
By outsourcing data scientists, organizations tap into a pool of seasoned experts who deeply understand analytics, predictive modeling, and ML. This step expedites the deployment of skilled professionals, allowing organizations to kickstart data-driven initiatives and realize quicker returns on investment. Unlike in-house teams that might be involved in multiple tasks, outsourced data scientists are focused solely on data-related tasks, ensuring outputs come with higher quality and accuracy.
The era of robotic computer language has evolved into something truly remarkable. Thanks to advancements in technology like Natural Language Processing (NLP), we’ve moved far beyond the rigid and mechanical interactions with computers. Gone are the days when communication with technology felt inorganic and distant.
Through speech recognition and reinforcement learning, modern AI can now grasp the context of conversations and adapt its responses accordingly. Computers can respond to human language and customize interactions in a natural and intuitive way. For instance, chatbots, virtual assistants, and voice-activated devices have become human-like companions able to engage in meaningful conversations, understand context, and provide helpful responses.
NLP has found applications in various industries, from customer service and healthcare to finance and entertainment. And as the demand for NLP soars, outsourcing NLP engineers has become an increasingly viable and strategic option for businesses looking to harness this transformative technology.
There is, however, one caveat: Hiring, training, and retaining in-house NLP engineers can be costly and time-consuming. Fortunately, outsourcing allows you to leverage external expertise without the overhead costs associated with full-time employees. It also empowers you to jumpstart your NLP projects by tapping into a ready-to-go team of experts, significantly cutting down on your project’s time-to-market.
Computer Vision Engineer
With visual information dominating our digital landscape, computer vision has emerged as a groundbreaking technology with diverse applications – from self-driving cars to medical imaging.
Computer vision engineers, who deeply understand ML, image recognition, and algorithm development, play a massive role. But businesses struggle to fill the role due to an unfortunate shortage in the engineering industry and tech. As a result, outsourcing computer vision engineers has gained traction.
Service providers often have pre-assembled teams with the required expertise, facilitating faster project initiation. By outsourcing computer vision tasks, companies can free up their in-house teams to focus on their core competencies and strategic initiatives, enhancing overall efficiency.
Unlike ML engineers who ensure infrastructure, such as computing resources and data pipelines, ML researchers are focused on exploring and developing machine learning algorithms, models, and techniques that form the backbone of ML systems.
These researchers are trained to advance the theoretical foundations of ML. They develop new algorithms and methodologies designed to solve complex problems and improve the overall capabilities of ML systems. Additionally, they conduct experiments to gauge their algorithms, often benchmarking to compare their innovations with existing approaches.
Through outsourcing, businesses can access top-tier talent without the financial burden of maintaining a large in-house team. Collaborating with researchers from across the globe introduces fresh perspectives and innovative approaches. Different cultural backgrounds and experiences can lead to creative solutions that might not have been discovered in a homogenous environment.
By tapping into a diverse pool of experts, organizations can drive forward their ML initiatives, discover novel solutions, and remain competitive in a rapidly evolving landscape.
Advantages of Outsourcing AI and ML
From cost savings to scalability, let’s explore the reasons why AI outsourcing is the best strategy to stay ahead of the curve.
Access to Expertise
As AI’s popularity grows, businesses find themselves in a quandary — struggling to recruit employees equipped with specialized skills. Almost half (42%) of organizations have admitted to a lack of the skill sets needed to manage their current tech systems effectively.
Reports further show that demand will rise steadily in the coming years. Sadly, there aren’t enough qualified people for these highly technical roles. While entry-level positions might be easier to fill, securing experts is more challenging.
Fortunately, outsourcing can help. By entrusting your AI projects to a reliable team, you gain the advantage of expertise often elusive in the current landscape. Collaborating with these specialists offers direct involvement in the project’s progression and provides you with insights and developments as they unfold.
Many businesses outsource for a simple yet profound reason: cost reduction.
Deloitte reveals that it is the biggest global outsourcing driver (70%). This strategic maneuver allows businesses to channel their resources towards core competencies, innovation, and growth while ensuring operational efficiency. It is particularly true in tech since nearly half of IT leaders struggle to control and predict costs.
Thanks to the well-structured agreements and clear cost structures of BPOs, businesses can sidestep the challenges of financial unpredictability and navigate a smoother course toward their AI aspirations.
However, ultimately, it’s not just about cost savings — it’s about leveraging expertise and resources to navigate the technology landscape while maximizing your financial resources.
Data Management and Governance
Nearly half of IT leaders cited their existing operating models as a barrier in adapting to unforeseen circumstances and making sound business decisions. While data management can help in this challenge, the complexity of this task poses yet another conundrum.
Managing big data is not merely a task; it’s a multifaceted responsibility that spans from data collection to compliance.
But the journey doesn’t stop there. The collected data demands continuous cleaning, analysis, and interpretation. Sensitive data requires added layers of protection to ward off potential breaches and security vulnerabilities. All these complexities ripple through budgets and resources, potentially overwhelming existing employees.
Enter outsourcing — a strategy that shifts the responsibility to experts well-versed in data management, security, compliance, and governance. Instead of grappling with the intricacies of data architecture and the ever-present specter of breaches, businesses can lean on the expertise of their outsourcing partners.
By entrusting data management, security, and compliance to experts, businesses can channel their resources towards innovation, strategic decisions, and achieving AI-driven outcomes with confidence.
Focus on Core Competencies
Success hinges on an organization’s ability to juggle many tasks, from strategy formulation to customer engagement. Focusing on core competencies in this intricate balancing act stands as your North Star.
The advantages of outsourcing in this context are two-fold. First, it alleviates the strain of managing intricate AI projects, freeing internal teams to focus on the company’s strengths. Second, it provides access to AI experts who are immersed in the intricacies of the field, ensuring that the AI projects are executed with precision and excellence.
Businesses can channel their resources and expertise towards activities that define their unique value proposition by entrusting AI initiatives to specialized service providers.
Core competencies encompass the strengths and capabilities that set a business apart in the marketplace. These represent what a company does best, the driving force behind its competitive advantage. By honing in on these strengths, businesses can channel their resources and efforts into areas that directly contribute to their growth and success.
Scalability and Flexibility
Scalability, the art of expanding operations seamlessly in response to growing demands, remains a common challenge for businesses of all sizes. Unfortunately, research shows that only 55% of IT leaders can effectively scale their operations. However, with the rapid pace of technological advancements, businesses must navigate the complexities of scaling without compromising quality or straining resources. This is another compelling reason why you should outsource AI.
As your business scales, the demand for AI solutions will experience sudden spikes. Fortunately, AI outsourcing companies offer flexible resource allocation, seamlessly adjusting your workforce to meet increased workloads without disruptions.
At its core, outsourcing is not just a strategy — it’s a pathway to unlocking untapped potential and a conduit for your business to thrive in an ever-changing business landscape.
Key Considerations in AI and ML Outsourcing
Outsourcing can indeed be a powerful strategy for businesses looking to leverage the benefits of AI and ML without the burden of building an in-house team. However, several critical considerations must be taken into account to ensure a successful outsourcing partnership.
Data Security and Privacy
As businesses venture into outsourcing, one fundamental principle reigns supreme: data security and privacy.
A resounding 68% of outsourcing companies eyeing a shift to cloud technology cite data security as their top concern. This sentiment resonates loudly in the AI and ML arena, where data is not just an asset, but the lifeblood of innovation.
As businesses expand their global footprint, they encounter a mosaic of data privacy legislation that governs the protection of employee and customer data. These regulations, such as the General Data Protection Regulation (GDPR), extend far beyond borders, requiring meticulous attention to detail in cross-border data transactions.
When outsourcing AI and ML projects, the scope of data transport and storage magnifies. Data, often traversing the globe, must be securely transported and stored. If your internal IT team adheres to strict data access requirements — like robust authorizations, VPNs, or access tokens — these must seamlessly integrate with the outsourcing partner’s systems.
Communication and Collaboration
Effective communication and collaborative partnership always take center stage in outsourcing. More than just mere elements, these are the foundation for outsourcing success.
Confusion finds no place to hide when needs and goals are meticulously defined. In projects with numerous and unpredictable variables, the risk of miscommunication and subsequent rework looms large. This friction, the discord between your internal team and the outsourcing service provider, can cast shadows over results and undermine progress.
Regarding AI and ML outsourcing, regular, transparent communication is not a luxury; it’s a necessity. Clear communication forms the bridge that connects project requirements, progress, and potential roadblocks.
However, effective communication and collaboration don’t happen by chance; they are crafted through deliberate efforts. Clear lines of communication must be established, with both parties committed to regular updates, discussions, and adjustments.
Ultimately, your outsourcing partner should be an extension of your team, closely working with you, not just for you.
Expertise and Performance Quality
The journey toward excellence begins with the choice of a trustworthy outsourcing partner.
Before embarking on an AI and ML outsourcing partnership, businesses must comprehensively evaluate the vendor’s capabilities. This evaluation goes beyond surface-level assessments, delving deep into the heart of the vendor’s expertise in AI and ML technologies.
Start by scrutinizing the vendor’s team. Expertise is a collaborative endeavor, and the prowess of the vendor’s team plays a pivotal role in project success. Investigate their experience, qualifications, and track record with previous projects. Case studies, client testimonials, and references offer a panoramic view of their ability to deliver impactful AI solutions.
When businesses align with outsourcing partners with a strong foundation of expertise and a history of quality performance, they set the stage for success. This partnership isn’t just about delegation – it’s about collaboration, synergy, and a shared vision for transformative AI solutions.
Why Nearshore AI Services in Colombia?
Colombia offers a unique combination of cost efficiency and a skilled workforce, making it an ideal outsourcing destination. With its competitive labor costs, you can access highly qualified professionals and top-notch services at a cost advantage. It also has a growing tech talent pool fuelled by top-ranking universities that produce highly-skilled graduates ready to join the workforce.
Colombia’s strategic location also provides a favorable time zone overlap with North America and Europe for seamless collaboration. But what truly sets this top nearshoring hub apart is its cultural affinity with Western business practices for smooth communication and collaboration.
Additionally, its government also actively supports foreign investment and business partnerships – offering incentives, tax benefits, and a supportive regulatory environment for outsourcing ventures.
Unlock the Power of Artificial Intelligence and Machine Learning Through Outsourcing
Don’t let the AI revolution pass you by. Embrace the future with confidence and efficiency by outsourcing your AI and ML projects to our experienced team.
With over a decade of expertise in the industry, SuperStaff has established itself as a prominent BPO service provider with a strong presence in Colombia. We boast a talented pool of professionals proficient in a wide range of BPO services. From customer support to back-office processes and advanced AI and ML solutions, our team is well-equipped to handle diverse business requirements.
Contact usnow to embark on a transformative AI journey!
Coming from a media background, Anca leverages her knowledge of the intricacies of Philippine international relations and the cultural nuances of Filipino people to bring valuable insights into how these factors birthed the country’s successful BPO industry.