Shenzhen-based AI² Robotics – which has raised “hundreds of millions of yuan” in funding investment – is emerging as a notable player in the advanced automation space, focusing on what they term “embodied AI”.

This approach seeks to empower physical entities, like their innovative robots, to intelligently learn from and interact with their surroundings.

A compelling example of their work is the Alpha Bot, a sophisticated machine that integrates an autonomous mobile robot base with a dual-armed collaborative system, and a humanoid torso and head, designed for versatility in complex environments.

Leading this charge is AI² Robotics’ founder and CEO, Eric Guo Yandong. With a vision to develop truly general-purpose robots, Guo is steering the company towards creating adaptable machines capable of tackling tasks across diverse sectors, from manufacturing and logistics to, eventually, everyday household assistance.

His ambition is to see these intelligent robots become as ubiquitous as personal computers.

AI² Robotics describes its Alpha Bot as ‘a general-purpose intelligent robot’

RoboticsAndAutomationNews.com is pleased to offer our readers an in-depth look at AI² Robotics’ vision and progress, thanks to an unofficial transcript provided directly to us by CNBC.

The following conversation features Eric Guo Yandong speaking with Christine Tan, a seasoned anchor for CNBC’s flagship morning programme, Squawk Box Asia.

Christine Tan: Our next guest is from AI² Robotics, a Shenzhen-based tech startup that focuses on what they call embodied AI – that’s a type of AI that combines technologies to enable physical entities such as robots and smart cars to learn and to interact with its environments.

The company’s founder and CEO, Eric Guo Yandong joins us now from the sidelines of the Nomura Investment forum Asia 2025. Eric, good to have you with us. Nice to see you.

Now, I’m just so amazed, I think we’re all amazed at how sophisticated robotic technology has evolved over the years. We’re now talking about humanoid robots.

Now for the lay person, can you explain to us, can you tell us what that means in terms of functions, in terms of what it means intelligence? What does it mean?

Eric Guo Yandong: Well, good morning everyone. This is Eric Guo Yandong. I’m the founder and CEO of AI² Robotics. We are developing general purpose robots.

So the key part behind general purpose robots is model called embodied AI foundation model. With this model, the robot can understand people’s order, can perceive different environment and can perform tasks all by its own.

So we developed a model called embodied AI foundation model, which is very different from the ChatGPT model developed by OpenAI.

The most different part is that our model has better spatial intelligence, so that our model can see the environment better.

The second part is that the output of the model is numerical action signals directly to control the robot.

It not only answers or videos or images generated by the model, the model itself can generate numerical action signals. With the help of this model, we can let the robot do pretty much any tasks.

So we are using our robots in scenarios including warehouses, manufacturing and gradually to households, maybe someday on Mars.

CT: That’s funny, Eric, but you know, it could be the case one day, right? To what extent are your humanoid robots entering the very competitive industrial production lines? What’s the adoption rate like?

GY: Well, there are several key things you need to consider to develop general purpose robots. One part is you need to have the best embodied foundation model.

The second part is to have a stable and lower cost hardware design. Third part, as you just said, you need to push your robot into real scenarios. Let people use it. The more people use it, the smarter your robot will be.

So nowadays, we already signed contract with top-tier car manufacturers, with semiconductor factories and biotech factories, as well public service later on this year, if you visit some airports In China, you will see our robot serving people.

CS: You think what you’re developing, the humanoid robots? Do you think you can compete with the big four that’s out there?

I’m talking about ABB, the Kuka, the Fanuc and Yaskawa. Do you think you can give them a run for their money?

GY: Well, this is a great question. So I think the humanoid or general-purpose robot is essentially a new generation of intelligent device. This type of device is invented after the large model area.

So as a new company focusing on the general-purpose robot, I think we do have advantage in this area. The Big Four, for example like ABB, they have their own advantage in maybe industrial usage or the single function usage.

So, the advantage of our robot is that we can do complex tasks, or we can let our robot learn new things very quickly, and our robot will have this kind of common sense.

For example, if you need to find a cold coke, our robot will turn to refrigerators and open the refrigerator and get the coke for you.

It’s a different type of thing we are developing, very different from the big four companies.

CS: Eric, you just completed a series A funding as a startup. What are the challenges, securing the kind of investor that you need to help you develop the robotics that you need?

GY: Well, there are several things or challenges to push forward our product. The first one is to get the top talents all over the world.

We just set up collaboration with Peking University, one of the top universities in China, and I also got my degree from Purdue University, I’m very grateful to my PhD advisors.

The key element to win in this war is to get top talents. And second part is that, as you just said, you need to get enough funding to polish your product.

I think a more efficient way is to let people use it and get data back, as well as get some cash back, and this is more effective, efficient way to keep running a company, rather than just raising funds.

CT: Eric, can you tell us the next big thing you’re working on in the labs? Is it going to be a big game changer in the humanoid robotics market?

GY: Well, I think there are several things we are working on. One of the things we just announced is that we let our robots can do manipulation and navigation together.

We do this kind of joint optimization so that robot, our robot can do more things. Another thing is that our robot can do (are) very complex tasks, and can reasoning horizon tasks, for example making breakfast.

Not only make breakfast around the kitchen, but we can let the robot get all the materials you need to get your breakfast, make breakfast for you and deliver breakfast to your table.

This is very new, and we look forward to delivering this product to every single family.

You know, when I worked with Microsoft, the dream used to be put every PC on every family’s desk. Now, AI² Robotics, we dream to put one robot for every single family.

CT: Wow, sounds like it’s going to replace humans one day. It’s one of those things. Watch out!

GY: I think it’s a tool to improve the productivity.

CT: Okay, nice talking to you. Great stuff. Thank you so much for being with us.

Ready for that long-awaited summer vacation? First, you’ll need to pack all items required for your trip into a suitcase, making sure everything fits securely without crushing anything fragile.

Because humans possess strong visual and geometric reasoning skills, this is usually a straightforward problem, even if it may take a bit of finagling to squeeze everything in.

To a robot, though, it is an extremely complex planning challenge that requires thinking simultaneously about many actions, constraints, and mechanical capabilities. Finding an effective solution could take the robot a very long time — if it can even come up with one.

Researchers from MIT and NVIDIA Research have developed a novel algorithm that dramatically speeds up the robot’s planning process. Their approach enables a robot to “think ahead” by evaluating thousands of possible solutions in parallel and then refining the best ones to meet the constraints of the robot and its environment.

Instead of testing each potential action one at a time, like many existing approaches, this new method considers thousands of actions simultaneously, solving multistep manipulation problems in a matter of seconds.

The researchers harness the massive computational power of specialized processors called graphics processing units (GPUs) to enable this speedup.

In a factory or warehouse, their technique could enable robots to rapidly determine how to manipulate and tightly pack items that have different shapes and sizes without damaging them, knocking anything over, or colliding with obstacles, even in a narrow space.

“This would be very helpful in industrial settings where time really does matter and you need to find an effective solution as fast as possible. If your algorithm takes minutes to find a plan, as opposed to seconds, that costs the business money,” says MIT graduate student William Shen SM ’23, lead author of the paper on this technique.

He is joined on the paper by Caelan Garrett ’15, MEng ’15, PhD ’21, a senior research scientist at NVIDIA Research; Nishanth Kumar, an MIT graduate student; Ankit Goyal, a NVIDIA research scientist; Tucker Hermans, a NVIDIA research scientist and associate professor at the University of Utah; Leslie Pack Kaelbling, the Panasonic Professor of Computer Science and Engineering at MIT and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL); Tomás Lozano-Pérez, an MIT professor of computer science and engineering and a member of CSAIL; and Fabio Ramos, principal research scientist at NVIDIA and a professor at the University of Sydney. The research will be presented at the Robotics: Science and Systems Conference.

Planning in parallel

The researchers’ algorithm is designed for what is called task and motion planning (TAMP). The goal of a TAMP algorithm is to come up with a task plan for a robot, which is a high-level sequence of actions, along with a motion plan, which includes low-level action parameters, like joint positions and gripper orientation, that complete that high-level plan.

To create a plan for packing items in a box, a robot needs to reason about many variables, such as the final orientation of packed objects so they fit together, as well as how it is going to pick them up and manipulate them using its arm and gripper.

It must do this while determining how to avoid collisions and achieve any user-specified constraints, such as a certain order in which to pack items.

With so many potential sequences of actions, sampling possible solutions at random and trying one at a time could take an extremely long time.

“It is a very large search space, and a lot of actions the robot does in that space don’t actually achieve anything productive,” Garrett adds.

Instead, the researchers’ algorithm, called cuTAMP, which is accelerated using a parallel computing platform called CUDA, simulates and refines thousands of solutions in parallel. It does this by combining two techniques, sampling and optimization.

Sampling involves choosing a solution to try. But rather than sampling solutions randomly, cuTAMP limits the range of potential solutions to those most likely to satisfy the problem’s constraints. This modified sampling procedure allows cuTAMP to broadly explore potential solutions while narrowing down the sampling space.

“Once we combine the outputs of these samples, we get a much better starting point than if we sampled randomly. This ensures we can find solutions more quickly during optimization,” Shen says.

Once cuTAMP has generated that set of samples, it performs a parallelized optimization procedure that computes a cost, which corresponds to how well each sample avoids collisions and satisfies the motion constraints of the robot, as well as any user-defined objectives.

It updates the samples in parallel, chooses the best candidates, and repeats the process until it narrows them down to a successful solution.

Harnessing accelerated computing

The researchers leverage GPUs, specialized processors that are far more powerful for parallel computation and workloads than general-purpose CPUs, to scale up the number of solutions they can sample and optimize simultaneously. This maximized the performance of their algorithm.

“Using GPUs, the computational cost of optimizing one solution is the same as optimizing hundreds or thousands of solutions,” Shen explains.

When they tested their approach on Tetris-like packing challenges in simulation, cuTAMP took only a few seconds to find successful, collision-free plans that might take sequential planning approaches much longer to solve.

And when deployed on a real robotic arm, the algorithm always found a solution in under 30 seconds.

The system works across robots and has been tested on a robotic arm at MIT and a humanoid robot at NVIDIA. Since cuTAMP is not a machine-learning algorithm, it requires no training data, which could enable it to be readily deployed in many situations.

“You can give it a brand-new problem and it will provably solve it,” Garrett says.

The algorithm is generalizable to situations beyond packing, like a robot using tools. A user could incorporate different skill types into the system to expand a robot’s capabilities automatically.

In the future, the researchers want to leverage large language models and vision language models within cuTAMP, enabling a robot to formulate and execute a plan that achieves specific objectives based on voice commands from a user.

This work is supported, in part, by the National Science Foundation (NSF), Air Force Office for Scientific Research, Office of Naval Research, MIT Quest for Intelligence, NVIDIA, and the Robotics and Artificial Intelligence Institute.

Fleets of bio-inspired robots and cutting-edge automation are gearing up to address the ocean’s plastic plague and chemical contaminants, with nature’s own microscopic powerhouses offering a complementary strategy.

The challenge of ocean pollution is vast, a tidal wave of plastics, chemical effluents, and debris threatening marine ecosystems and, ultimately, human health. Traditional cleanup methods, while valuable, often struggle with the scale and complexity of the problem.

But a new generation of innovators is looking to robotics and automation, drawing inspiration from nature itself, to turn the tide.

From nimble robotic fish targeting microplastics to autonomous surface vessels scooping up debris, the future of ocean cleanup is looking increasingly automated, with intriguing possibilities for commercial deployment.

Robo-aquatics: Engineering nature’s cleanup crew

The vision is compelling: swarms of intelligent, autonomous robots diligently patrolling our oceans, detecting and removing pollutants with unprecedented efficiency. This isn’t science fiction; it’s the burgeoning field of environmental robotics, and several pioneering concepts are already making waves.

1. Tiny robot fish: A microplastic marvel in the making

Imagine a small, agile robot, just a few centimetres long, designed to navigate aquatic environments with the grace of a real fish.

This is the concept behind various research initiatives, including a notable project from Sichuan University in China. Their light-activated, self-healing robotic fish, though still in early developmental stages, is designed to adsorb microplastics from the water.

• How it works (conceptually): These tiny bots, potentially made from materials that attract and bind to microplastic particles, could be deployed in targeted areas. Their fish-like movement allows for efficient navigation through complex environments. Some designs incorporate materials that can repair themselves if damaged, increasing longevity.
• The automation aspect: The true power lies in swarm capabilities – thousands of these robots operating in coordinated fleets, communicating data on pollution hotspots and collection status. Future iterations could autonomously return to a mothership for “offloading” collected plastics and recharging.
• Commercial potential: While still largely in the R&D phase, the demand for effective microplastic removal solutions is immense. Companies able to scale production of such robots, ensuring their biodegradability or effective retrieval, could tap into a significant environmental services market. The key will be cost-effectiveness, durability, and demonstrable impact. Short, compelling video clips of these prototypes in action have already proven highly shareable, hinting at strong public and investor interest.

2. WasteShark: Autonomous surface cleaning

Moving from micro to macro, Netherlands-based RanMarine Technology has already brought an autonomous solution to market with its WasteShark.

This autonomous surface vessel (ASV) operates much like a floating vacuum cleaner, collecting plastics, algae, and other floating debris from waterways.

• Current capabilities: The WasteShark can operate for up to 8 hours on a single charge, collecting as much as 500 kg of waste (depending on the model) and gathering water quality data. It uses GPS and other sensors for navigation and can be remotely monitored and controlled.
• Commercial traction: WasteSharks are being deployed in marinas, ports, and urban waterways globally. This demonstrates a clear commercial application for robust, automated cleanup solutions in controlled environments. The business model includes sales, leasing, and data services.
• Future development: Enhancements could include AI-powered debris recognition for more targeted cleaning, improved swarm operations for larger areas, and integration with automated waste disposal systems.

3. Seabed sentinels: Robotic crabs and crawlers

Not all pollution floats. The seabed is often a repository for heavier debris and contaminants. Here, bio-inspired robots mimicking crabs or other benthic creatures are being explored.

For instance, researchers at institutions like the Korean Institute of Ocean Science and Technology (KIOST) have developed concepts like the “Crabster” series – multi-legged robots designed for underwater exploration and manipulation tasks on the complex and often unstable seabed.

• Targeted action: These robots could potentially identify, grasp, and remove specific items of debris, or even perform in-situ remediation of contaminated sediments. Their legged design offers stability and manoeuvrability where wheeled or tracked robots might struggle.
• Automation and development: The challenge lies in autonomous navigation in deep, dark, and unstructured environments, as well as providing sufficient power for extended missions. However, advancements in underwater sensors, AI-driven pathfinding, and robotic manipulation are steadily progressing.
• Commercial niche: While likely more expensive and complex than surface cleaners, specialized seabed robots could find commercial applications in industrial cleanup (for example, around decommissioned offshore structures), archaeological recovery, or targeted environmental remediation projects.

Nature’s microscopic allies: A biological boost

While robotics offers engineered precision, the natural world has its own microscopic janitors. Scientists have identified various bacteria and fungi with the remarkable ability to degrade pollutants, including plastics.

A prime example is Ideonella sakaiensis, a bacterium discovered in Japan that can break down polyethylene terephthalate (PET), the plastic commonly used in beverage bottles. This microbe produces enzymes that essentially “eat” the plastic, converting it into more benign substances.

The commercial angle here lies in biotechnology – harnessing these microbial processes. This could involve developing industrial-scale bioreactors where these organisms break down collected plastic waste, or even in-situ applications where microbial consortia are introduced to contaminated environments.

While the large-scale, open-ocean application of such organisms faces significant ecological and efficiency challenges, their role in controlled waste processing or targeted bioremediation is a promising avenue for commercial R&D.

Intriguingly, future advancements could see a closer intersection between these fields, perhaps with robots deploying or monitoring bioremediating agents, or even incorporating biological components for sensing or degradation directly into their design.

Navigating the path to cleaner oceans

The journey towards automated ocean cleanup is not without obstacles. For robotics, these include:

• Scaling and cost: Moving from prototypes to economically viable, large-scale deployments.
• Power and durability: Ensuring robots can operate for extended periods in harsh marine conditions.
• Ecological impact: Designing robots that are themselves non-polluting and do not harm marine life.
• Retrieval: Ensuring that at the end of their life, robots can be retrieved and don’t become part of the problem.

For biological solutions, challenges involve efficiency, controlling their spread in natural environments, and public acceptance.

However, the pace of innovation in robotics, AI, materials science, and biotechnology is rapid. Increased investment, interdisciplinary collaboration, and supportive regulatory frameworks can accelerate the development and deployment of these technologies.

The commercial opportunities are significant, spanning robot manufacturing, operational services, data analytics, and biotech applications.

An automated horizon of hope

The vision of robotic fleets and microbial allies actively healing our oceans is a powerful one. While the scale of pollution is daunting, the ingenuity being applied to develop these automated and biological solutions offers a new wave of hope.

For the robotics and automation industry, cleaning and protecting our marine environments represents not only a profound challenge but also a significant frontier for innovation, development, and ultimately, commercial success in building a more sustainable future.

The global in-vitro fertilization (IVF) market, valued at over $26.5 billion in 2023 and projected by some analysts to exceed $35 billion by 2030, is at the point of a technological revolution.

New York-based Conceivable Life Sciences is positioning itself at the vanguard of this transformation, developing what it claims is the world’s first end-to-end automated, AI-powered IVF laboratory.

This innovation promises to not only disrupt existing methodologies but also significantly expand market reach by tackling critical barriers of cost, accessibility, and scalability.

The current IVF landscape, despite its advanced medical science, relies heavily on manual, “artisanal” lab processes, as described by Conceivable.

These intricate procedures, often involving over 200 steps, are not only labor-intensive but also contribute to the high cost of treatment – averaging around £7,500 in the UK and $15,000-$20,000+ per cycle in the US.

Consequently, as Conceivable’s investor, Artis Ventures, points out, an estimated “80 percent of infertile couples go untreated, unable to access IVF because of high cost, proximity to care, or both”.

This vast, underserved segment represents a significant growth opportunity for disruptive technologies.

Conceivable aims to unlock this potential by “synthesizing AI and robotics to automate the more than 200 intricate steps required to create embryos”.

Their system is designed to perform delicate procedures like intracytoplasmic sperm injection (ICSI) with robotic precision, and has even demonstrated the world’s first fully automated ICSI performed remotely – with an embryologist in New York controlling the process for reproductive cells located 3,000 miles away.

This capability, showcased at the 2024 European Society of Human Reproduction and Embryology (ESHRE) conference, highlights the sophistication of their robotics, advanced optics, machine vision, and AI integration.

The company reports that even in early testing, its clinical outcomes “rival the best IVF labs in the world”, citing 22 pregnancies achieved upon the first embryo transfer in a prior Institutional Review Board (IRB) study.

A commercial pilot, including a 100-patient IRB study, is currently under way in Mexico City, with a US launch targeted for early 2026.

The investment proposition: Scaling for an untapped market

This technological prowess has attracted significant investor attention. Conceivable Life Sciences has raised over $39 million to date, including an $18 million Series A financing round led by Artis Ventures.

Stuart Peterson, founder and managing partner at Artis Ventures, said: “Conceivable’s approach to IVF… will transform the field worldwide, catalyzing a new era of quality, scale, accessibility, and follow-on innovation.”

The core of the investment thesis lies in dramatically improved efficiency and scalability. By automating labor-intensive tasks, Conceivable aims to substantially reduce operational costs.

Future Positive Capital, an investor, indicates the company’s goal is to “reduce the price of IVF by 70 percent”.

Taking a conservative US average cost of $15,000 per cycle, a 70 percent reduction would bring the price down to approximately $4,500, making treatment accessible to millions more. This isn’t just about cost savings; it’s about market creation.

Aike Ho, a partner at ACME Capital, another investor, reinforces this: “Our mission at Conceivable is to make IVF affordable to everyone who needs it… Conceivable’s innovation will radically increase accessibility to IVF and achieve better clinical outcomes for patients.”

The company also suggests its model will enable OB/GYN partners to offer IVF services without the substantial capital expenditure of setting up traditional labs.

The evolving lab: Human expertise meets robotic efficiency

The advent of such comprehensive automation naturally raises questions about the role of highly skilled embryologists.

However, rather than outright replacement, the technology is poised to address existing constraints, such as the current shortage of embryologists (with an estimated 400 openings in the US in 2022).

Automation can handle the repetitive, high-volume tasks, allowing embryologists to transition to roles involving oversight of multiple automated systems, quality assurance, interpretation of AI-driven data analytics, managing complex cases, and focusing on research and development.

This shift could significantly increase the number of cycles an embryologist can effectively manage, enhancing lab throughput and alleviating workforce bottlenecks that currently cap growth in the industry.

The demand for engineers and scientists skilled at the intersection of biology, robotics, and AI is also likely to increase.

The AI edge and competitive horizon

Conceivable emphasizes its “AI-powered reinvention” of the lab. While full details of the AI’s role are proprietary, its application in machine vision, precision robotic control, and process optimization is key.

As this technology matures, further AI development could lead to more personalized treatment protocols and enhanced predictive analytics for embryo viability, further solidifying the system’s value proposition.

While other companies are developing AI tools for specific IVF tasks like embryo selection, Conceivable’s claim to an “end-to-end automated IVF lab” positions it as a potentially transformative force, aiming to redefine the operational standards for fertility clinics globally.

The journey from manual artistry to automated precision in the IVF lab is well under way. For engineers, investors, and the broader healthcare market, Conceivable Life Sciences represents a compelling example of how robotics and AI can not only optimize complex processes but also democratize access to life-changing medical treatments, unlocking significant market potential in the process.

Most employee development programs fall short because they forget the most important part: the person behind the plan. When training feels generic, employees tune out—and companies miss the mark on impact.

Employees want growth that reflects who they are and where they’re headed. But when programs ignore individual goals, they feel disconnected. And when those same programs aren’t tied to business priorities, it’s no surprise the results fall flat.

HR Trends Report: How personalized development will accelerate business growth in 2025 >>

Your people want more than check-the-box training. They want opportunities that actually fit—ones that reflect their strengths, spark their interests, and help them grow. They want leaders who back their career development, not just in words but in action. And they want clear, honest paths to move forward in their careers—paths that align with both their goals and the company’s direction.

Though 78% of executives say building capabilities is key to long-term success, only 30% believe their current efforts are actually working. Why the gap? Many organizations still treat learning and development as an HR side project, rather than a true business priority.

“We need to help leadership see that development isn’t just for development’s sake—it’s about preparing for the future. We don’t always have the luxury of teaching people what they need in advance—we often don’t know what’s required until the moment we need it. That’s why continuous learning and agile development are more critical than ever to spark true creativity and innovation.”

– Teresa Preister, Senior Insights Analyst, Quantum Workplace

With 88% of companies citing retention as a top concern, learning and development has become a leading strategy for keeping top talent. Organizations that view this demand as an opportunity—not a burden—retain high performers 98% more effectively and are 57% more prepared to navigate change.

Winning organizations go beyond intent. They operationalize development through structured yet flexible career pathing—outlining clear next steps that align employee goals with business needs. That structure drives real ROI and secures leadership buy-in.

“One of the biggest challenges with programs like this is proving ROI. But when senior leaders see outcomes from employees’ ideas, it shifts their perspective. Learning becomes tangible, and that momentum helps push initiatives forward. Plus, it directly impacts retention and engagement by making employees feel valued and included.”
– Julie Melidis, Director of Learning & Development, Benesch

Developing employee talent as intentionally as you build products or services requires commitment. But the future belongs to the organizations that do. Companies that invest in personalized development don’t just retain talent—they build a workforce that’s agile, aligned, and ready for whatever comes next.

Why employee growth & development is broken (and how we’re fixing it!)

Four critical shifts reshaping employee development

Organizations are facing a major evolution in how employee development must be designed and delivered. Here are four critical shifts driving the change:

1. Learning happens on the job.

On-the-job learning is the engine of employee growth. Today’s workforce expects development to be tailored to their roles, goals, and pace—and they want it embedded into their day-to-day experience. In fact, McKinsey estimates that 40–60% of an employee’s human capital value comes from skills learned through experience. 

Learning isn’t linear—and employees find the most value in immersion, application, and iteration.

The 70/20/10 model underscores this shift:

• 70% of learning happens through hands-on experience
• 20% through coaching and mentorship
• 10% through formal training

Gone are the days of “check-the-box” learning—where development meant sitting in a classroom or earning a certificate that didn’t translate into real impact. While formal training still plays a role, it can’t carry the load. Many organizations still rely on outdated models that disconnect learning from the flow of work—missing huge opportunities for continuous, on-the-job skill building.

“The most effective learning isn’t something employees have to find—it’s something that finds them. Growth should be part of the workday, reinforced in real time, and connected to real business challenges. If development feels like just another task, it won’t stick. But when learning happens naturally and adds value immediately, it drives real behavior change.”
– Meghan Freeman, Product Manager, Quantum Workplace

2. Employees want more control over their careers.

Today’s employees want more than vague promises of opportunity. They want to own their career journey—and clearly see what’s next.

That means organizations must provide visibility into growth paths, guidance on how to advance, and support from leaders and managers at every level. When HR builds career pathing frameworks, trains managers to coach effectively, and promotes transparency around opportunities, employees feel more in control and more invested.

But it doesn’t stop with HR. Senior leaders must champion growth as a business priority—celebrating internal mobility and signaling that career advancement is valued.

Organizations that win create a culture where growth isn’t feared or hidden—it’s expected, supported, and celebrated.

3. Growth takes many paths.

Career development doesn’t look like a ladder anymore. It’s not always upward—and that’s a good thing.

Top organizations understand that growth takes many shapes: lateral moves, expanded responsibilities, cross-functional projects, and new experiences that build long-term value. It’s not about chasing titles—it’s about increasing impact.

Since 2021, internal mobility has increased by 30%, and companies with strong internal hiring programs see employees stay 41% longer.

“Leaders must actively champion and celebrate lateral growth, recognizing it as a strategic advantage—not a sidestep. When employees see their peers gaining new opportunities and being rewarded for them, they feel more confident making similar moves.”
– Aaron Brown, Senior Insights Analyst, Quantum Workplace

When you redefine what growth looks like, you unlock a more adaptable, engaged, and future-ready workforce.

4. Technology opens access to growth.

Employees want development that adapts to them—not the other way around. 58% of employees prefer to learn at their own pace, on demand. They expect personalization that only technology can deliver.

That’s where tech becomes a true enabler. AI-powered career coaching delivers real-time, individualized recommendations—guiding employees toward skills to develop, projects to pursue, and mentors to connect with. It moves development from once-a-year conversations to a dynamic, ongoing experience.

With the right technology, development becomes more accessible, more relevant, and more effective—for every employee, at every level.

Delaying investments in employee development is a business risk in 2025.

HR’s role is stretching. You’re balancing tighter budgets, higher expectations, and constant pressure to prove business impact. And you’re doing it while wearing every hat in the closet: strategist, coach, technologist, change agent.

That’s why clarity matters. Acting with focus—and connecting your growth-minded employees to the right resources—is what turns development from a nice idea into real results.

But time isn’t on your side. Three major forces are reshaping the landscape right now:

• AI and emerging tech are transforming how work gets done
• An aging workforce is accelerating succession needs
• Ongoing talent shortages are making internal development mission-critical

These aren’t future challenges. They’re here now. The organizations that respond with strategy, structure, and urgency will come out ahead.

The cost of inaction around employee growth & development

1. Top talent walks out the door.

Many employees feel completely on their own when it comes to career development. Nearly half (46%) say their manager doesn’t know how to help them grow—and only 15% say their manager has helped create a career plan in the past six months.

If this is happening in your organization, you can bet that your best people are not far from leaving. When employees don’t see clear growth opportunities, they go looking for them elsewhere. 75% of exited employees say no one discussed their growth in the three months leading up to their departure.

And the cost isn’t just in morale—it’s in dollars. Every resignation means lost productivity, recruiting expenses, onboarding time, and valuable knowledge walking out the door. Replacing an employee costs 50% to 200% of their salary—a burden that adds up fast.

Organizations that get this right don’t just keep people—they keep the right people. In fact, companies with structured, business-aligned development programs are 98% more likely to retain high performers.

Employees aren’t just looking for jobs. They want to work somewhere they can grow, contribute, and feel momentum. If you don’t show them a future at your organization, they’ll find it somewhere else.

2. Managers struggle to coach effectively.

Managers sit at the center of employee development—and too often, they’re the missing link. Many don’t have the time, tools, or training to coach effectively. Some even hold back high performers—not out of malice, but out of fear. They’re worried about losing their best people, so they unintentionally stall growth instead of supporting it.

“Some employees are lucky to have great managers who guide their development, but that’s rare,” notes Meghan Freeman, Product Manager at Quantum Workplace. “Many managers lack the time, skills, or structure to do this well. AI could bridge the gap—providing timely guidance, surfacing key information, and keeping development top of mind in ways human oversight often can’t.”

Organizations that win don’t leave coaching to chance. They give managers the tools, training, and confidence to have real growth conversations. They use AI to prompt those conversations when it matters most. And they build a culture where supporting internal movement isn’t risky, but rewarded.

3. High-potential employees stay hidden and underutilized.

It’s a familiar pattern: doing the same thing again and again—and expecting different results. That’s how many organizations approach internal mobility. 

The issue usually isn’t a lack of talent. It’s a lack of visibility. When lateral moves or cross-functional opportunities aren’t encouraged—or worse, aren’t even acknowledged—employees hesitate to raise their hand. And that hesitation keeps high-potential talent hidden, underused, and eventually, disengaged.

Encouraging internal movement is one of the fastest ways to unlock growth—both for your people and your business. But visibility alone won’t cut it. You need structure. That means building clear paths for employees to stretch into new roles, try out projects in other teams, and grow in ways that actually match their interests and strengths.

Technology can help here. AI-powered tools can surface tailored suggestions for roles, mentors, and skills to build—making it easier for employees to take the next step.

4. L&D investments lack ROI.

Only 30% of executives believe their development programs deliver real business impact. That’s not just a learning problem, but a business problem.

Many programs fall flat because they’re generic, hard to scale, and rarely tied back to what matters most: performance, retention, and business growth. From 2022 to 2024, fewer than 5% of capability-building programs matured enough to even measure success. In a time of tighter budgets and growing expectations, that kind of return just doesn’t cut it.

At the root of it all is misalignment. If your employee development strategy isn’t clearly connected to real business outcomes, it starts to look like a nice-to-have instead of a must-have. And that makes it a prime target when budgets tighten. 

So don’t just think about how to build your program this year—think about how you’ll build proof that it’s working. Without clear ROI, you risk losing leadership support, momentum, and the infrastructure your future-ready talent strategy depends on.

HR trends to action: investing in personalized employee development

Personalized employee development doesn’t have to be a massive overhaul—and it doesn’t have to wait. Here are four moves you can make this quarter to build momentum:

1. Equip managers to become career coaches.

Your managers are the single most powerful driver of employee growth—and often the least supported. Give them the tools, training, and confidence to lead better career development conversations.

Start small: offer simple coaching frameworks, clear conversation guides, and AI-driven prompts to spark meaningful check-ins. When managers feel equipped, they’re far more likely to take action—and that consistency builds a stronger, more connected development culture.

2. Redefine success beyond promotions.

Not all growth looks like a promotion—and your culture should reflect that. Encourage employee development opportunities like lateral moves, cross-functional projects, and skill-building as real, valuable career progress.

Celebrate employees who take on stretch roles or make sideways moves to grow. Share their stories across internal channels to reinforce that progress isn’t always vertical—but it’s still progress.

3. Embed development into daily work.

Learning sticks when it’s applied. Use AI-powered insights, skills-based learning, and just-in-time coaching to connect employee goals with real business challenges.

Start by identifying one key initiative in each department where employees can contribute and grow at the same time. Build cross-functional teams and tie learning goals to business outcomes. When development feels real, employees stay engaged—and results follow.

4. Invest in the right employee development technology.

Look at your employee development tools with fresh eyes. Does your current tech stack support personalized, continuous growth—or just check the box?

The best platforms surface growth opportunities automatically, offer AI-powered skill assessments and coaching, and make impact measurable for both employees and leaders.

Look for employee development solutions that don’t just deliver content—but guide progress, spark conversations, and make development easier to manage and easier to see.

The real question isn’t whether you can afford to invest in development—it’s whether you can afford not to. Every day you delay is another day a competitor might be building stronger talent, keeping employees more engaged, and creating a workforce that’s ready for whatever comes next.

Want more actionable insights?

Explore all seven trends shaping the future of work in our 2025 Workplace Trends Report. You’ll find practical strategies to strengthen your talent pipeline, boost engagement, and drive real results—today and tomorrow.

Germany is set to host the European Humanoid Robots Summit on November 17-18, 2025, an event poised to explore the burgeoning field of humanoid robotics and its potential to alleviate critical labour shortages across Europe and redefine industries.

Organised by ACG Events, a professional event organiser focused on industry-relevant sectors, the summit aims to create a highly efficient collaborative platform for the global humanoid robotics and embodied intelligence industries.

The event comes at a crucial time, as Europe grapples with an intensifying dual crisis of an ageing population and systemic labour deficits.

A recent McKinsey report highlights that labour shortages in several countries, including Germany, have reached critical levels, with job vacancies outnumbering unemployed individuals.

Humanoid robots are emerging as a revolutionary solution to this workforce scarcity, offering the potential to reshape industrial paradigms and social infrastructure, thereby driving sustained market optimism.

The European Humanoid Robots Summit will adopt a hybrid online-offline format, enabling global participation and the synchronisation of market insights with cutting-edge technological trends.

The agenda promises a deep dive into several key areas, including technological frontiers and innovative breakthroughs in humanoid robotics.

Discussions will also cover product design and viable commercialisation pathways, alongside crucial considerations of the societal impact and ethical governance surrounding these advanced technologies.

Furthermore, the summit will focus on future ecosystem development and strategic positioning within Europe’s rapidly evolving humanoid robotics industry.

A significant draw for attendees will be the presence of major industry players. Companies already confirmed to participate include investment banking giant Goldman Sachs, automotive leader Geely Auto, and robotics pioneers AgiBot, Boston Dynamics, and Unitree.

Tech titans Nvidia and Huawei Cloud, alongside industrial manufacturing stalwart Siemens, are also slated to attend, promising a rich exchange of ideas and potential collaborations.

The European Humanoid Robots Summit 2025 offers a vital platform for experts, industry leaders, and policymakers to convene and accelerate the coordinated development of humanoid robotics, a field with the potential to significantly impact Europe’s economic and social future.

SmartThings continues to invest in the Developer Center with tools for partners such as Test Suite, Product Cloning, and Certification by Similarity to simplify product integration and certification for a single product or an entire portfolio. After obtaining Works with SmartThings (WWST) certification, Analytics helps our partners gain valuable insights about how users interact with their products.

With the goal of making integration easy for partners, SmartThings added another tool in the integration process called the Device Profile Builder, allowing partners to specify a device’s capabilities and how it interacts within the SmartThings ecosystem.

“We’ve heard from developers that they wanted an easier way to build their devices with SmartThings. A tool with an intuitive user-friendly interface that would work for any device” says Nate Porras, Senior Product Manager at SmartThings. “We feel like we accomplished that with Device Profile Builder.”

SmartThings currently offers Device Profile Builder for Cloud integrations and soon for Direct Connected and Mobile Connected integrations.

“Device Profile Builder is nicely designed and straightforward to use.  You can create a Device Profile effortlessly.  We are always trying to find the simplest way to integrate, and Device Profile Builder is a key tool in that process.”

Anthony Richardson, QA Engineer at August Home

Read on to learn about Device Profile Builder and how to get started.  

Device Profile Builder

SmartThings Device Profile Builder is a web-based tool that assists developers with creating Device Profiles, which define a device and its features on the SmartThings platform through Capabilities. It contains the Components – which is a group of SmartThings Capabilities – and metadata (ID, name, ownership, and more) of a device, defining how a device on the SmartThings platform behaves. For example, with a light, the component contains four common Capabilities for lights including Switch, Switch Level, Color Control, and Color Temperature.

Use Device Profile Builder to:

• Define how you want your products to look to users in the SmartThings app
• Set SmartThings Capabilities for each of your products

 Get Started

How to use the SmartThings Device Profile Builder:

1. Visit the Products section in the SmartThings Certification Console where you can add a new product or edit an existing one.Under Integration Details / Device Capabilities, click Create a profile here. Or here is the direct link to the Device Profile Builder.
2. Click the button Add new Device Profile and enter a unique name. 
3. Add your Capabilities and Components. You can also use product category specific templates to make the process faster.
4. Use the Dashboard View to set how you want your product’s icon, action, and state to look in the SmartThings App. 
5. Click Create Profile. After Creating, you will have options to View, Publish, Edit, Clone, Download File, Upload file, and Delete under the Actions menu.
6. Publish your Device Profile and use it to finish creating your product. Then submit your product to obtain the Works with SmartThings (WWST) certification.

You can re-use a device profile for similar products or create as many variations as you need for your portfolio of products.

Use Device Profile Builder when Creating a Product

Below is the Create Product section in the Certification Console.

When creating a product in the Certification Console, you can use Device Profile Builder to add your device profiles. Under Integration Details / Device Capabilities, click Create a profile here or Edit an existing profile. 

After finishing Adding a Product in the Certification Console, you can Test it Using Test Suite, and then go on to Submit it for Works with SmartThings Certification (WWST).

Here are images from the Device Profile Builder. We’ll use the Capabilities for your devices as part of the Works with SmartThings certification. 

Templates

Get started faster with Templates. Templates are prebuilt sets of required and suggested Capabilities for common product types that help you create your device profile effortlessly. Simply select a product type and apply it to your component.

Download / Upload File

For even more customization, you can use the Download / Upload File functions to modify the JSON file. If you have a more complex scenario you want to configure, this functionality gives visibility into all the fields. For example, this can be useful for certain devices that have specific preference thresholds or operating limits, which can be configured for normal or alarm states. There is also an ability for more granular control of what your device looks like in the SmartThings app.

Want to integrate your products with SmartThings? Visit our Developer Center to get started and access Device Profile Builder.