Choose Technologies with an Intuitive Interface to Increase Employee Adoption

Velocity KSA Interview with Dr Jassim Haji - President - Artificial Intelligence Society

Dr Jassim Haji, President of the Artificial Intelligence Society, delves into the future of work, exciting AI breakthroughs and how enterprise leaders can navigate the ever-evolving landscape of AI responsibly and ethically.

In a captivating interview, Dr Jassim Haji, President of the Artificial Intelligence Society, discusses the metrics for tech investment success, aligning people with technology, promoting employee adoption of AI, and the future of work. 

Discover how enterprise leaders can harness the potential of AI responsibly and fairly while exploring groundbreaking advancements in AI technology that are shaping our world. Stay informed and enlightened with valuable insights from a visionary leader in artificial intelligence.

Excerpts from the interview;

What metrics do businesses need to track to show the success of tech investments?

The success of tech investment is reflected in its return on investment (ROI). A positive ROI indicates that the investment has generated additional value for the company, showcasing its success. Furthermore, ROI helps businesses evaluate the risk associated with the investment by considering future returns, helping them to make well-informed decisions.

Tracking employee productivity gains is crucial when introducing new technology into the workflow. The efficiency of a company relies on the productivity of its workforce. Therefore, investing in technology that improves time-saving measures and enhances productive processes within the company is essential to demonstrate the system’s success.

Metrics such as better customer experience, employee adoption rates of the new technology (indicating its user-friendliness), reduced employee error rates, and shorter project life cycles are all significant indicators businesses should track. These metrics provide valuable insights into the success rate of tech investment, highlighting its positive impact on the company’s operations and outcomes.

How can teams align people and processes to maximise tech investments?

The first step in any new tech investment is to establish the business vision and communicate the goals associated with introducing the new technology. It is important to consider the existing workflows, identifying areas that can be enhanced, focusing efforts on delivering better outcomes for internal and external stakeholders. The key objective here is to align people, processes, and technology as an interconnected system that collaborates towards a shared business objective.

To effectively integrate the new technology into current processes, it is necessary to develop a comprehensive roadmap that outlines the specific requirements for implementation. This roadmap should encompass the necessary adjustments to people, processes, and workflows. The technology can seamlessly integrate into relevant workflows, enhance capabilities, and encourage greater user adoption.

Continuous monitoring, measurement, iteration, and technology improvement are essential. These activities help identify gaps and refine the technology, making it more efficient. This iterative approach increases the likelihood of success in aligning people and processes, thus maximising the utilisation of the technology.

How can businesses increase employee adoption of technology?

User-friendliness is a crucial criterion when considering the adoption of any new technology. The technology should possess an intuitive interface with clear instructions and documentation for employees, ensuring ease of use, navigation, and learning. Implementing a concise and comprehensive training program that highlights the purposes, benefits, and experiences associated with the new technology is essential. It also contains on-demand training allowing the employees to learn at their own pace.

To increase adoption rates, it is vital to establish a well-supported feedback channel that enables employees to report issues and suggest improvements to the new technology. Addressing concerns and implementing necessary changes based on employee feedback encourages ongoing engagement and facilitates continuous learning and skill development related to the technology.

Seamless integration of the new technology into existing workflows and processes is paramount to minimise disruptions and ensure a smooth transition towards its incorporation. When the new technology is an upgraded version of existing processes and can reduce employee workload, it positively impacts the workflow, motivating employees to embrace and adopt the technology.

Please share any recent breakthroughs or advancements in artificial intelligence that you find particularly exciting or promising.

The AI revolution is driving rapid technological advancements with profound effects. A prime example is the emergence of Generative Pre-trained Large Language Models, which can generate remarkable human-like text based on questions or prompts. These models have showcased impressive capabilities in natural language processing, content generation, translation, and even coding assistance. Combined with the immense potential of quantum computing, they promise to significantly enhance AI’s capabilities and expand its scope, effectively leveraging both technologies’ strengths to overcome their limitations.

Another area of great interest and advancement is the development of self-driving vehicles. These vehicles are becoming increasingly adept at navigating roads and avoiding obstacles through advancements in deep learning, computer vision, and precise sensors like high-resolution cameras, radar, and LiDAR. Although still in the nascent stages of research and development, self-driving vehicles promise to make transportation safer, more efficient, and more accessible.

Additionally, a field with immense potential for artificial intelligence is the development of innovative medical applications. There are ongoing efforts to design models to identify and create potential new drugs, diagnose diseases, develop novel treatment methods, and personalise medical care based on individual patient’s genetic makeup and medical histories. By tailoring treatments to specific patients, these applications can significantly improve treatment effectiveness while reducing the risks of side effects.

What skills should enterprise leaders develop to be prepared for the future of work in tandem with AI?

Artificial intelligence is an invaluable asset for enterprises. However, leaders must possess the ability to think critically, logically, and analytically when interpreting outcomes. They should actively seek relevant questions, carefully evaluate the responses and associated data in accordance with their business objectives. Additionally, leaders should be able to identify and scrutinise the evidence presented and draw better conclusions to determine the most effective course of action.

Data lies at the core of AI. Enterprise leaders should ensure they understand the data utilised to train AI models and how to leverage it for making well-informed decisions. A strong understanding of emerging technologies will empower leaders to effectively adopt and implement new AI systems.

The intuition of a strategic and long-term vision is very important for enterprise leadership. They must align AI initiatives with their organisation’s objectives, identifying opportunities where AI can generate value, foster collaborations and innovation, and elevate the customer experience. By doing so, they can effectively transform their industry and organisation.

How can enterprise leaders ensure that artificial intelligence is used responsibly and fairly without reinforcing existing biases or creating new ones?

Enterprise leaders should prioritise transparency regarding the modelling of AI systems. They should know about the algorithms employed, the datasets used, and the potential for biases within the developed models. Establishing strict guidelines and actively avoiding biased datasets during AI model training is crucial, ensuring a process that upholds transparency and ethics.

To further ensure responsible AI usage, involving stakeholders at every stage of the development process is important. Considering feedback from stakeholders allows for refining the AI algorithms, guaranteeing that the technology is fair, inclusive, and aligned with user expectations.

Engaging in an external auditing process and assessment can provide validation that helps build trust with customers, employees and the broader community. A third-party organisation should conduct this auditing independently, and they should certify the AI system to be non-biased or discriminatory.

With generative AI taking on more cognitive labour in coding, what skills should data science professionals focus on?

Data scientist professionals can contribute their expertise, ensure ethical practices, collaborate with diverse teams and deepen their understanding of specific domains they work on. They need to understand and solve the problem by identifying the dataset that can be used to create the AI model using generative AI.

Effective communication with the stakeholder is a valuable skill set that all data scientists need to possess. They must be able to convey complex ideas to both technical and non-technical audiences, ensuring clarity and conciseness in their explanations and building trust with stakeholders.

Even though generative AI may automate the coding aspect, a data scientist is responsible for cleaning, processing, integrating and storing data essential to prepare high-quality datasets that would help the generative AI train the model.

What is the main goal of the Artificial Intelligence Society, and how do you achieve this?

The primary objective of the Artificial Intelligence Society is to advance responsible AI development, ensuring a human-centric approach and minimising potential risks. It actively promotes the establishment of ethical AI principles and practices, upholding the public’s right to understand and participate in governing AI systems. Furthermore, it encourages the responsible adoption of AI in government and businesses.

We believe it is important for people to understand and accept the uses of AI in their everyday life and ensure that the AI is utilised ethically. It helps ensure that people and other business organisations can leverage the benefits of AI while making informed decision making, and promoting AI adoption.

The society conducts workshops, seminars and training programs to achieve these goals and promote ethical guidelines to address vital issues such as privacy protection, biases, accountability and transparency in AI systems. Moreover, the society arranges collaboration among AI researchers, practitioners, policymakers and other stakeholders, fostering interdisciplinary discussions to exchange ideas and explore innovative AI applications. 

Active engagement with policymakers is a core focus of the society. It supports policymakers by sharing expertise and insights, advocating for a forward-thinking, balanced, and responsible use of AI technology in policy formulation and decision-making.

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