Artificial intelligence (AI) has become an important technology tool and has created a dynamic landscape in which organizations can adapt to disruption, leverage existing technologies, and pursue other emerging trends. This is an area of rapid progress, widespread adoption, and limitless opportunity.
According to HCLTech’s 2024 Tech Trends report, the AI landscape will evolve towards a revolution, with generative AI (GenAI) giving way to large-scale proofs of concept, driving rapid progress and new advancements in of ethical AI. As organizations embrace the challenges and opportunities of advanced AI technologies, many are seeing its transformative and disruptive influence on industries.
Evaluate the impact of AI
HCLTech invests in developing GenAI capabilities through co-creation with customers and leveraging engineering expertise. According to Alan FlowerExecutive Vice President and Head of Cloud Native and GenAI Labs, HCLTech and HCL CTO for Cloud Native, GenAI has garnered considerable attention.
“We hope this exciting time continues and opens a new frontier of possibilities,” says Flower. “The coming year will be crucial for the creation of new AI applications and the growth of existing ones.”
The current stage of AI, according to research conducted by HCLTech, is that of disruption. Clearly, organizations are addressing the challenges and opportunities presented by advanced AI technologies, leading to a substantial percentage (41%) of organizations in the disruptive category. Additionally, 32% are currently in the “Hype” stage and 27% are in the “Adoption” stage.
Additionally, 55% of respondents in the HCLTech study believe that GenAI is leading the revolution in the overall AI segment and 28% believe that GenAI will play a transformational role for companies over the coming years.
The trending AI landscape
The current AI landscape can be segmented into three parts: ethical AI, generative AI, and machine learning (ML). According to research, ML has the highest adoptability factor and along with Generative AI and Ethical AI, both microtrends are poised to disrupt the market and generate hype over the next year , respectively.
What are these microtrends and what do they mean for the growing global AI landscape? Ethical AI was designed and developed with the greatest respect for human values and ethics and has become a central point where all advances in AI converge before being adopted on a large scale. Ethical AI adheres to well-defined ethical guidelines, such as respecting individual rights, protecting privacy, avoiding discrimination, and preventing manipulation.
GenAI is a type of AI that creates different types of content, such as text, images, audio, or data, in response to prompts or input. GenAI uses algorithms to generate new content and recent advancements have made it easier to use with user-friendly interfaces. Nearly half of respondents (48%) believe that content generation will be the most relevant use case for GenAI and a majority of respondents, 58%, also believe that machine learning is at the top of the list. adoption in the global AI segment.
Finally, machine learning is a branch of AI that allows computers to learn from data without explicit programming. Rather than following rigid instructions, ML algorithms analyze massive data sets, discover patterns, and make predictions or decisions based on the knowledge gained from that analysis.
Ethical AI sees great potential
Ethical AI is a priority for many organizations today to grow their businesses, but also due to legislation and regulations being implemented to address AI concerns. Recently, the EU announced a provisional agreement on a AI Law with the aim of paving the way for a global AI landscape that is ethical, safe and trustworthy. In October, the Biden administration released a draft AI Bill of Rights that aims to guide the design, use and deployment of automated systems.
Companies implementing AI will need to consider the ethical component of the emerging technology, while being mindful of increasing legislation in various regions around the world. Those already working on AI ethical frameworks will be best able to adapt to the changing regulatory landscape.
The benefits that ethical AI brings to society make it a good candidate for exploring new advancements in the AI landscape. The potential for ethical AI has great commercial value, including data privacy and security, bias mitigation, reliability and security. Ethical AI systems are designed to be impartial and avoid unfair discrimination. These systems provide equitable access and treatment, actively identifying and reducing bias related to factors such as race, gender or nationality, which is important for how organizations interact with their communities.
Need for ethical AI
Organizations will also need a clear AI ethics strategy in 2024, because without it they will face ineffective implementations. Developing a clear strategy will need to take into account regulatory barriers that vary across regions and sectors, which poses another challenge for its adoption.
Ethical AI also places a strong emphasis on data security by establishing strong data governance and model management practices to protect sensitive information, ensuring user privacy, while adhering to AI principles . Ethical AI systems also operate reliably and safely, limiting their functions to their intended purposes. This approach reduces the likelihood of unexpected incidents or errors, bringing great business value to the landscape.
Ethical AI may be in the hype stage, but getting to the adoption stage will require overcoming some challenges. Because ethical AI is new and complex, its integration can be difficult due to limited familiarity. High-quality data for ethical AI systems is also essential, but it is difficult to obtain and maintain, potentially biasing AI results.
Additionally, ethical AI introduces cybersecurity risks that must be mitigated to protect data and systems.
GenAI in the disruption phase
GenAI is a disruptive tool with the strongest impact on socio-cultural environments, as well as work environments. For example, Microsoft’s co-pilot is an “everyday AI companion” that has made 88% of developers using GitHub Copilot more productive, according to Microsoft, and 74% say they can now focus on more satisfying work. This represents a key factor for GenAI adoption: employee productivity.
“Generative AI is set to have a profound impact on many industries,” says Madhumit Dixit, senior vice president of central engineering and technology. “This will augment core processes within these sectors by leveraging AI models, and influence support processes that extend across organizations, affecting areas such as marketing, design, communications “business, training and software engineering.”
GenAI can create creative content at scale and reduce the need for significant manual labor and through automation, while saving time and operational costs. It also creates business value through personalized experiences by analyzing data to provide personalized recommendations and assistance with natural, human voices. GenAI automates complex processes, optimizes workflows, increases productivity and provides data-driven insights to help organizations be more efficient. But the true impact of its use cases still remains unclear. How far will GenAI go in areas like productivity? The industry will know more in 2024, as more organizations adopt technology to drive transformative change.
Some of the key factors driving the adoption of GenAI include how it enables organizations to stand out by creating unique content and innovative solutions; increases customer loyalty, satisfaction and engagement rates through personalized GenAI content and GenAI’s support for rapid experimentation, product development and idea exploration.
Through responsible implementation, AI has the potential to drive change across many industries and enable businesses to thrive in a rapidly changing landscape. By adapting to these disruptions, organizations can create new business models and seize limitless opportunities. We will continue to see innovation and adoption of AI technologies across all sectors and powerful new AI technologies, such as GenAI, ethical AI and machine learning, will enable businesses and organizations to overcome the challenges their sectors face. Additionally, the democratization of AI will allow it to reach more employees, becoming a tool with expanded possibilities and allowing businesses to be even better prepared for an unpredictable future.
