Agencies
The artificial intelligence industry is filled with impressive demo videos featuring robots doing flips and AI applications responding like humans. However, these demos often do not reflect the challenges of real-world applications.
AI solutions require time to mature, especially within organizations, where learning from data is a lengthy process. Mistakes and setbacks are common, which can lead to disappointment.While AI is expected to revolutionize industries, it’s crucial to remember that this transformation will take time.
In 2023, global investments in AI startups reached approximately $42.5 billion, with the United States leading with $67.2 billion, followed by China with $7.76 billion.
One of the key drivers attracting investors is the rapid advancement in generative AI. Investments in this area grew fivefold in 2023 compared to the previous year, with industry giants like OpenAI and Anthropic securing significant portions of the funds. OpenAI, for instance, received over $10 billion in investments.
AI demos typically operate under perfect conditions, showcasing the potential of systems. However, there is a significant gap between demos and real-world implementations.
Organizations often encounter challenges when trying to implement AI projects. These challenges make scaling and deploying AI solutions difficult. In 2023, 214 new AI unicorns – companies valued at over $1 billion – emerged, creating an additional $35 billion in value.Sectors such as health care, finance and customer services are poised for significant transformations due to AI.
For AI models to function effectively, they require vast amounts of high-quality data. However, organizations often face issues with incomplete, inconsistent, or poor-quality data.
Cleaning and organizing this data is time-consuming and costly, requiring organizations to make substantial investments. Moreover, data must be used in compliance with ethical and legal standards. AI projects also demand significant computing power and storage capacity, often relying heavily on cloud resources.
Implementing AI projects requires a workforce skilled in data science, machine learning, and AI. Many organizations lack these competencies.
Retaining AI talent is challenging for many companies, and complying with legal regulations and industry-specific rules can slow down AI projects, especially in industries like health care, finance, and the public sector. Organizations must collaborate with legal and ethical experts to ensure compliance.
TT Ventures, the venture capital arm of Türk Telekom, has invested in global AI initiatives, including the AI company Cohere, through the Digital Transformation Capital Partners (DTCP) fund.
Cohere recently secured $450 million in funding, bringing its valuation to $5 billion.
TT Ventures’ General Manager Muhammed Özhan emphasized the company’s role in shaping the future by investing in global AI startups like Cohere, which is expected to bring technological innovation to Türkiye.
“Through Türk Telekom Ventures, we not only help move Turkish startups abroad but also play a key role in shaping the future by investing in groundbreaking global ventures.
We closely follow global developments, particularly in transformative fields like generative AI, which is impacting the world,” said Özhan.
“One such investment is in Cohere, a company leading in this space. We are thrilled that Cohere’s innovations will contribute significantly to our country and the broader technology ecosystem.
As with any innovation, AI adoption often faces resistance. Typically, experts who are trying something for the first time are met with skepticism. Cultural resistance within organizations can make AI adoption challenging.
Employees may worry that AI will either take over their jobs or alter their roles. Therefore, institutions must emphasize that AI will complement human labor, and they should develop change management strategies to ease this transition.
AI applications, however, can make incorrect decisions or produce biased outcomes, making ethical responsibility and accountability crucial concerns.
Organizations must ensure that AI systems operate ethically and transparently, and they should implement oversight processes to maintain control over these systems.
While small-scale AI projects may perform well in demos, they often face scalability issues when applied to complex real-world processes.
Successfully scaling AI solutions across an entire organization requires careful planning and development of scalable technologies.
Consulting firms and research organizations regularly publish studies on the challenges of AI implementation.
McKinsey’s annual report, titled The State of AI, explores how AI is being used in corporate environments and highlights key obstacles. This report also provides in-depth insights into scaling AI projects and integrating them into business processes.
Deloitte’s reports, particularly those from 2023, highlight the challenges faced during AI adoption and how to overcome them. Key focus areas include data management, workforce competencies, and compliance.
Similarly, Gartner’s “Hype Cycle for Artificial Intelligence, 2023” explores the maturity levels of AI technologies, addressing the challenges of implementing AI projects and the journey these technologies undergo to reach full maturity.
Istanbul and Boston-based artificial intelligence startup Novus has successfully closed its seed investment round, securing $1.5 million in funding.
Led by the Gelecek Etki Fund, managed in partnership with Vestel Ventures and Tacirler Portfolio Management, the round also saw participation from Sabancı Ventures, Inveo Ventures, DeBa and several international funds.
With the latest funding, Novus has reached a valuation of $14 million.
