Dmytro Afanasiev, AI innovator and CEO, on why empowering people, not changing them, is essential to actual enterprise affect.
Synthetic intelligence has had an enchanting journey within the enterprise setting since 2018. Again then, cutting-edge corporations began experimenting with enterprise course of automation, however most implementations had been restricted to easy algorithms and primary types of machine studying. After the explosive development in implementations and beneficiant investments, 2021-2023 noticed a part many specialists name the “AI Disappointment.” Firms that invested thousands and thousands in AI-based automation discovered that the expertise didn’t at all times stay as much as expectations: ROI (Return on Funding) was decrease than predicted, implementation was extra advanced than imagined, and a few techniques designed to exchange people solely created new issues as a substitute of fixing outdated ones.
This journey has been intently noticed by entrepreneurs like Dmytro Afanasiev, who started making use of AI parts in his tasks as early as 2017 with the creation of Dentist24.on-line – a SaaS system for dental clinics. Afanasiev, founding father of a number of profitable expertise corporations and developer of an revolutionary system for optical recognition, verification, and unification of seamen’s paperwork (patent filed in 2021, with approval anticipated in summer season 2025), has witnessed AI’s evolution from experimental expertise to mainstream implementation.
In keeping with Gartner’s 2024 Hype Cycle for Synthetic Intelligence report, about 60% of enormous corporations that invested in Generative AI – algorithms that may create new content material together with textual content, photos, audio, and video based mostly on coaching information – in 2022-2023 didn’t obtain the anticipated ROI because of the improper method to implementing the expertise. That stated, IDC predicts that world AI spending will attain $300 billion by 2026, however the focus will shift from full automation to integrating human expertise with the advantages of AI.
As we speak, in 2025, we’re seeing a shift to a extra mature understanding of AI’s position in enterprise. The important thing query turns into not “How can we replace humans with machines?” however fairly “How can we use AI to empower humans?” This shift from pure automation to augmentation—utilizing expertise to increase or improve human capabilities fairly than exchange people—is defining a brand new part of digital transformation.
“Automation and augmentation are fundamentally different approaches. In the first case, we try to exclude humans from the process. In contrast, in the second case, we amplify their capabilities and make them more efficient,” explains Afanasiev. His present undertaking, Seamensway, the place he serves as CEO and co-founder, and the Crew Administration System platform his workforce is growing, embody the ideas of augmentation in maritime recruiting, demonstrating how AI can increase, not exchange human experience.
Anatomy of “AI Disappointment”
The interval of “AI disappointment,” which happens after the preliminary wave of enthusiasm for introducing synthetic intelligence, has goal causes. As Dmytro Afanasiev factors out, based mostly on his expertise working with varied industries, many corporations face the identical issues when implementing AI applied sciences.
“Most organizations approach AI from the position of full automation, seeking to replace people with algorithms. But practice shows that the technology is not yet ready to fully take on complex tasks, especially those that require contextual understanding and decision-making under uncertainty,” explains Afanasiev.
In his work with maritime recruitment and coaching, Afanasiev examines the processes of AI implementation in corporations of various sizes. His method relies on actual instances from his intensive expertise in each the maritime and SaaS industries.
“The human factor is critical to the success of AI projects. When we exclude people from the process and rely entirely on algorithms, we lose the tacit knowledge and experience gained through years of practice. This knowledge cannot be fully formalized and transferred to a machine,” Afanasiev notes.
In keeping with the 2024 MIT Expertise Overview, corporations utilizing an augmentative method to AI are, on common, 37% simpler at enhancing productiveness than these searching for full automation. Augmentation permits for the retention of uniquely human qualities—instinct, creativity, and moral considering—complemented by AI’s computational energy and analytical capabilities.
Engaged on automation tasks in maritime recruitment, Afanasiev has developed an method to process evaluation that determines the place full automation is simpler and the place augmentation is simpler. This method considers {industry} specifics, process complexity, potential dangers, and the necessity for human experience.
“Not every task requires full automation. Sometimes it is much more effective to use AI as a tool that empowers humans and makes their work more productive, but it leaves key decision-making to them,” Afanasiev emphasizes.
This method permits corporations to keep away from disappointment from AI implementation, because it units sensible expectations and focuses on creating actual enterprise worth fairly than implementing expertise for expertise’s sake.
The augmentation method in observe: Tweendeck and maritime recruitment
The augmentation idea involves life in Afanasiev’s present undertaking, Tweendeck, which was developed inside his firm, Seamensway. The platform addresses recruiting challenges within the maritime {industry}, a sector crucial to the worldwide economic system and logistics.
“The maritime industry is facing a serious skills shortage. According to the International Chamber of Shipping, the world will need around 89,510 additional new officers for ships by 2026. At the same time, recruitment processes remain highly inefficient, with a lot of paperwork and a high risk of errors,” Afanasiev notes.
The CMS (Crew Administration System) combines a number of superior applied sciences to resolve these challenges:
- A pc vision-based optical doc recognition system for automated information entry from maritime certificates
- Doc verification algorithms, together with verification by means of worldwide certificates registries
- Predictive analytics to evaluate candidate eligibility for place necessities
- Certificates validity monitoring and coaching planning techniques
The important thing innovation of this platform is its capability to speed up the processing of seafarer information by 70% in comparison with comparable options, utilizing a mix of pc imaginative and prescient, AI, and distinctive software program algorithms. This represents a big enchancment in effectivity for an {industry} that has historically relied on handbook doc processing.
Importantly, the platform doesn’t exchange recruiters however considerably expands their capabilities. It takes care of routine duties – processing paperwork, verifying certificates, monitoring deadlines – leaving it to people to make closing hiring selections the place expertise, instinct, and understanding of candidates’ gentle expertise are wanted.
The outcomes converse for themselves: Seamensway has skilled 3500% development in its first yr and has educated and licensed almost 10,000 seafarers, which represents roughly 10% of all energetic seafarers in Ukraine.
This sensible utility demonstrates the advantages of an augmentation method: as a substitute of attempting to completely automate the method, AI acts as a device to empower human specialists, main to higher outcomes with much less danger. Along with his sensible work, Afanasiev has contributed to educational analysis on the digital transformation of maritime logistics. His scientific article, “Big Data as a Tool for Increasing the Efficiency of Maritime Logistics Processes,” explores how superior information analytics and digital applied sciences can improve operational effectivity, scale back prices, and enhance forecasting accuracy in world delivery. This educational perspective additional reinforces the sensible options carried out by means of Tweendeck CMS.
From maritime experience to technical innovation
Afanasiev’s path to creating Tweendeck is grounded in his intensive expertise within the maritime {industry}. Earlier than founding Seamensway in 2020, he co-founded and led Crew Recruitment Companies (2007-2019), which grew to become one of many largest non-public recruitment corporations in Ukraine and the one one with the best to make use of Filipino seafarers.
This deep {industry} experience proved invaluable when growing technological options. With Crew Recruitment Companies, Afanasiev and his workforce managed to put over 10,000 seafarers on worldwide vessels, giving them distinctive insights into the complexities of crew qualification, doc verification, and the challenges of matching the best seafarers with the best vessels.
“Understanding the specific pain points of the industry from the inside was crucial for developing effective AI solutions,” says Afanasiev. “The maritime sector has its language, regulations, and workflows that would be difficult to grasp without direct experience.”
His earlier expertise creating SaaS platforms for dental clinics (Dentist Plus from 2015-2017 and Dentist24.on-line from 2017-2020) offered the technical basis for growing refined software program options. These earlier ventures, although in a special vertical, allowed him to develop experience in constructing scalable structure, creating user-friendly interfaces, and implementing subscription-based B2B software program merchandise.
The mixture of deep maritime {industry} information and software program growth experience uniquely positioned Afanasiev to handle the inefficiencies within the seafarer recruitment and certification course of. As he transitioned from managing Crew Recruitment Companies to founding Seamensway in 2020, he introduced with him a complete understanding of each the challenges confronted by the {industry} and the potential for technological options to handle them.
Moral dimensions of augmentation
Not like full automation, which frequently raises questions on job loss and depersonalization of labor, the augmentation method has different moral dimensions that require consideration. As Dmytro Afanasiev factors out, when growing augmentation options, a number of basic moral concerns should be taken into consideration:
- Transparency of algorithms – the person ought to perceive what the AI suggestions are based mostly on
- Equality of entry – applied sciences needs to be accessible to completely different classes of customers
- Preservation of human autonomy – people ought to retain the best to make the ultimate determination
- Information safety and privateness – particularly essential when dealing with seafarers’ private info
“In the US, the ethical aspects of AI adoption are fundamental due to strict regulatory requirements and high public awareness of digital rights. Any AI-based solution implemented in the US market must meet not only technical but also ethical standards,” Afanasiev notes.
In 2024, the US adopted new necessities for algorithm transparency and evaluation of their affect on society and enterprise. This makes the augmentation method notably related, because it includes sustaining human management over the decision-making course of. For Afanasiev, whose Tweendeck platform goals to develop into worldwide markets, together with america, adherence to those moral requirements is a key consideration in his product growth technique.
The way forward for human-machine symbiosis
Drawing on his expertise implementing AI within the maritime recruitment {industry}, Afanasiev predicts that by 2030, augmentation applied sciences will considerably rework the labor market. Instructional techniques will develop the talents that machines can’t: crucial considering, creativity, and emotional intelligence.
New professions are already forming on the intersection of conventional industries and AI: specialists in instructing industry-specific AI techniques, human-machine interplay analysts, and moral AI consultants. This confirms the pattern: AI just isn’t a lot changing current professions as creating new specializations.
For companies searching for to implement augmentation approaches successfully, Afanasiev affords 4 suggestions based mostly on his expertise with profitable implementations:
- Begin with a transparent enterprise objective fairly than expertise – determine particular enterprise issues that should be solved, and solely then choose expertise instruments
- Contain finish customers in any respect phases of implementation – contemplate the wants and expertise of those that will work straight with the system
- Develop workers’ digital expertise in parallel with expertise implementation – present the required coaching and help for efficient use of recent instruments
- Create a tradition the place expertise and other people complement one another – create an organizational setting the place each technological innovation and distinctive human qualities are valued
The Tweendeck platform exemplifies this philosophy, providing an end-to-end resolution for maritime recruiting that mixes the automation of routine processes whereas retaining human management over key selections.
“The true purpose of artificial intelligence is not to replace humans but to unlock their potential,” Afanasiev emphasizes. “In a world where technology is becoming more and more advanced, it is human qualities – empathy, intuition, creative thinking – that acquire the highest value. The future belongs to those who create a harmonious symbiosis between human and artificial intelligence.”
The augmentation method isn’t just a expertise pattern however a brand new philosophy of digital transformation that places individuals on the heart and makes use of expertise to empower fairly than exchange them. On this philosophy, corporations which have overcome the “AI disillusionment” are discovering a path to sustainably and successfully combine synthetic intelligence into enterprise processes. As Afanasiev demonstrates by means of his work with Seamensway and Tweendeck, when AI is designed to enrich human capabilities fairly than exchange them, each expertise and humanity can attain their full potential.
