How is AI being applied to business?

Artificial Intelligence is still an unfolding technology, and its complete influence and advantages remain untapped. AI breakthroughs are among various elements causing disruption in current markets and facilitating fresh digital business projects. Moreover, AI finds applications in diverse sectors, companies and roles in many ways.

Here are a few examples of AI application in business operations:

1. AI in Human-like Communications

Machine learning is paving the way for AI applications such as chatbots, autonomous vehicles, and smart robots that replicate human communications.

2. AI in Biometrics

Through deep learning techniques, AI provides solutions like facial recognition and voice recognition. Neural networks are used to hyper-personalize content through data mining and pattern recognition.

3. AI in IT Operations/Service Desk

AI facilitates IT support with Virtual Support Agents, ticket routing, information extraction from knowledge management sources, and providing answers to common questions.

4. AI in Supply Chain Management

AI assists with predictive maintenance, risk management, procurement, order fulfilment, supply chain planning, promotion management, and decision-making automation.

5. AI in Sales Enablement

AI can help identify new leads, nurture prospects through intelligent tracking and messaging, as well as improve sales execution and revenue through guided selling.

6. AI in Marketing

AI enables real-time personalization, content and media optimization, campaign orchestration, and uncovers new customer insights for effective marketing deployment.

7. AI in Customer Service

AI predicts customer needs and proactively deflects inquiries. Virtual customer assistants equipped with speech recognition, sentiment analysis, and automated quality assurance provide round-the-clock customer service.

8. AI in Human Resources

AI facilitates recruitment processes, skills matching, and leverages recommendation engines for learning content, mentors, career paths and adaptive learning.

9. AI in Finance

AI helps in dynamic processes requiring judgment and handling unstructured, volatile, high-velocity data. Examples include new accounting standards compliance, expense reports review, and vendor invoice processing.

10. AI in Sourcing, Procurement, and Vendor Management (SPVM)

AI assists in spend classification, contract analytics, risk management, candidate matching, sourcing automation, virtual purchasing assistance, and voice recognition.

11. AI in Legal

AI finds use in contract assembly, negotiation, due diligence, risk scoring, life cycle management, e-discovery, invoice classification, and more.

As enterprises adopt AI more widely, it’s inevitable that accompanying threats will arise, potentially posing significant risks to the organization. It’s crucial that these threats are assessed proactively to bolster stakeholder confidence in AI.

By 2025, it’s anticipated that regulations will demand greater emphasis on AI ethics, transparency and privacy. Far from inhibiting AI, these requirements will likely foster trust, stimulate growth and enhance the global performance of AI.


What is an Enterprise AI Strategy?

An enterprise AI strategy is a comprehensive plan that business leaders create to integrate Artificial Intelligence into their operations.

This strategy outlines AI use cases, weighs potential benefits and risks, aligns tech and business teams, and shifts organizational competencies to support AI implementation. Such a plan focuses on choosing AI initiatives that align with the company’s objectives and solves specific business problems.

As a company matures in its AI journey, the strategy evolves to address broader applications and greater impacts. Key components of this strategy include defining the AI vision, assessing and mitigating AI risks, crafting an AI strategic action plan, planning for AI adoption, and securing buy-in for the AI program.

Leveraging AI

To fully leverage the benefits of AI, business leaders must devise a holistic AI strategy. This strategy should pinpoint specific use cases, measure potential advantages and risks, synchronize tech and business teams, and shift organizational skills to bolster AI adoption.

Value extraction from AI requires strategic initiative selection, centered on your organization’s goals and the business challenges you aim to address. Integrating AI into your existing software suite is crucial for its success, and it is essential to harness data from all business segments to enhance its capabilities.

Companies in the early stages of AI maturity often focus on cost control use cases. As they advance in their AI journey, they start to explore other significant aspects such as improving customer experience. The application of AI becomes more widespread and impactful as AI maturity escalates.

1. Defining an Enterprise AI Strategy

For a company to seize AI advantages, executive leaders must craft a comprehensive AI strategy. This strategy should outline use cases, quantify benefits and risks, align business and IT teams, and modify organizational skills to promote AI adoption.

2. Selecting Strategic AI Initiatives

To extract value from AI, you should strategically select initiatives. These should align with your organization’s objectives and aim to solve specific business challenges. Successful AI implementation involves integrating AI into your existing software ecosystem and leveraging data from all business areas to power its features.

3. AI Use Cases

Typically, organizations in the early stages of AI maturity focus on cost control before moving on to critical elements such as customer experience. Research suggests that as AI maturity increases, its application broadens, and its impact becomes more significant.

4. Key Components of an Enterprise AI Strategy

AI Vision: Connect AI goals with enterprise aspirations. Clearly communicate how AI will support digital transformation objectives, encourage organization-wide AI fluency, and define success metrics.

AI Risks: Evaluate your potential risk exposure areas, including regulatory (privacy laws), reputational (AI bias), and organizational (lack of skills or infrastructure), and create mitigation plans.

AI Strategic Action Plan: Identify the effect on business models, processes, personnel, and skills. Adopt a portfolio approach to AI opportunities and assign responsibility for AI strategy development and execution. Interdisciplinary teams and data literacy are crucial for success.

AI Adoption: Define the use cases (such as human-like engagement, process optimization, insight generation) and use value maps and decision frameworks to prioritize adoption.

AI Program Buy-in: Promote the initiatives launch and celebrate its successes. Equip other C-suite leaders with the ability to share the AI team’s achievements.

Education News Uncategorized

Embracing AI in Education: Harvard’s New Approach

As we continue to navigate the ever-evolving landscape of digital technology, Artificial Intelligence has been making significant strides in various fields, including education. We are seeing significant shifts in higher education and we are witnessing the dawn of this new era.

AI: The New Catalyst in Education

Harvard University has recently announced its plans to leverage AI in its popular coding class. The intention is to enhance the educational experience, making it more immersive, intuitive, and interactive.

The university has introduced the “CS50 bot,” an AI tool bearing similarities to OpenAI’s ChatGPT. This sophisticated tool is designed to provide support to both professors and students, capable of answering common questions and offering feedback on code design and errors.

Striving for a 1:1 Teacher-Student Ratio

The ultimate objective behind this AI-powered initiative is intriguing. As Professor David J. Malan explains, Harvard University’s ambition is to use AI to approximate a 1:1 teacher-student ratio. This goal represents a radical shift from the conventional classroom model and leans heavily into a more personalized learning experience.

By providing round-the-clock software-based tools, students can receive academic support in a manner and at a pace that best suits their individual learning styles. This personalized approach to learning is expected to greatly enhance student understanding and engagement.

AI’s Role: Guide, Not Solve

While the CS50 bot will guide students towards answers, its function is not to simply provide solutions. The AI tool is designed to prioritize the cultivation of problem-solving skills and critical thinking capabilities, crucial competencies in today’s digital age.

The Future Jobs Report April 2023 by the World Economic Forum underscores this. The report indicates that as workplace tasks are increasingly automated, creative thinking and analytical thinking have become more important than ever before.

Conclusion: Is this Progress?

This move by Harvard University certainly represents a shift towards a more tech-forward and individualized approach to education. The introduction of AI in the classroom not only paves the way for personalized education but also nurtures essential skills in students, preparing them for the rapidly digitalizing workplace.

However, the question remains – is this progress? While we can appreciate the potential benefits, it’s crucial to consider the implications on traditional teaching methods and the possible challenges that may arise.

The intersection of AI and education is a dynamic and evolving frontier. As we continue to explore its possibilities, the focus should remain on utilizing these tools to foster a holistic and conducive learning environment.


Demystifying ChatGPT: Ten Key Questions Answered

OpenAI launched the chatbot and AI language tool, ChatGPT, in November 2022, and it has been a hot topic ever since. Despite the buzz surrounding ChatGPT and conversational AI, there are still several unanswered questions about what this generative AI can do for individuals and businesses. In this article, AI Ireland’s founder, Mark Kelly, provides invaluable insights into ChatGPT’s potential value and its safety for use and he also addresses the most common queries from AI Ireland’s clientele and members.


1. What is ChatGPT’s Role in the Enterprise?

ChatGPT, along with other foundational models, plays an integral part in hyperautomation and AI innovations. It automates, augments human or machine tasks, and autonomously executes business and IT processes. As such, it will likely redefine, recalibrate, and replace some tasks within various jobs.

2. What are the different Use Cases of ChatGPT?

From improving prose and code development to summarizing and classifying text, ChatGPT has numerous applications. It can also translate and convert language (including programming languages). Deployment methods include: using it as-is, prompt engineering without APIs, using APIs for prompt engineering, or custom building your version of foundational models.

3. What will be the impact of ChatGPT on the Workforce?

The workforce’s response to the introduction of tools like ChatGPT, hyperautomation, and other AI innovations will vary widely based on industry, location, enterprise size, and offerings. The use of these tools will primarily target repetitive and high-volume tasks, focusing on improving quality control and productivity. They will also be integrated into business applications to facilitate adoption and provide contextual information within applications.

4. What are ChatGPT’s Current Limitations?

ChatGPT’s training data only goes up until September 2021, meaning its knowledge of events since then is limited. Other limitations include its inability to cite sources, accept or generate image input, and train on personal knowledge bases. It cannot perform complex tasks; rather, it makes predictions. Its data privacy assurances have not undergone rigorous audits yet, and it cannot be relied on for math despite recent improvements.

5. What is the Security of Using ChatGPT?

While both OpenAI and Microsoft assure confidentiality and privacy of shared information, they have not yet fully clarified their data usage policies. Therefore, users should treat shared information as if it were public. To avoid shadow usage, companies should formulate a policy around ChatGPT, encourage innovation, monitor usage, and ensure the technology augments internal work with qualified data.

6. What does the future of ChatGPT and Generative AI look like?

Expectations for ChatGPT involve moving from its beta phase to early trials and pilots, where best practices for use will mature and adoption into business workflows will increase. However, this phase might also witness backlash over privacy, misuse of information, and bias.

7. What are the Recommended Actions?

While it’s still early days, the potential of this technology is immense. Users should encourage careful experimentation, understand the risks and best practices, and ensure all generated text is reviewed by humans. Form a task force to explore opportunities and threats, plan a discovery roadmap, and determine the skills, services, and investments needed.

8. How is ChatGPT trained?

ChatGPT is trained using a diverse range of internet text. But, it does not know specifics about which documents were in its training set or have access to any personal data unless explicitly provided in the conversation.

9. How reliable is the information generated by ChatGPT?

ChatGPT’s responses are generated based on patterns it learned during its training phase. It does not have the ability to access or retrieve factual, up-to-date information. Therefore, while it strives to provide useful and accurate information, it is always advisable to cross-verify the information from reliable sources.

10. Can ChatGPT replace human interaction?

While ChatGPT can mimic human-like conversation, it cannot replace human interaction. It lacks an understanding of context, personal experience, and common sense reasoning that is integral to human conversation.


“Unleashing the Power of Generative AI” with Kieran McCorry, National Technology Officer at Microsoft Ireland


In the latest episode of the AI Ireland podcast, Microsoft’s National Technology Officer, Kieran McCorry sheds light on the transformational impact of Generative AI and its integration into Microsoft’s overall products and service.

In the episode, Kieran emphasises the role of ChatGPT and its partnership with Microsoft Azure in making AI technology accessible to the masses. The discussion highlighted various applications of Generative AI, including its ability to assist users in creating PowerPoint presentations and even writing code.


AI: Enhancing Lives or Raising Concerns? Mark Kelly chats with Gerry Kelly on LMFM’s Late Lunch


Artificial intelligence has become a frequent topic in the news over the past couple of months as experts and tech leaders are cautioning about the potential consequences of their own AI inventions.

Our very own Mark Kelly recently sat down with Gerry Kelly on LMFM’s Late Lunch to chat about the current state of AI, its impact on society and whether AI should be feared or embraced as a means of enhancing human life.

Mark spoke to Gerry about how AI is already deeply embedded in various aspects of our lives. For example, Netflix utilizes AI to recommend shows based on users’ watch history, preferences, and demographics. This personalized experience is made possible through the use of recommendation engines that analyze user data. Mark also shared other examples such as in fraud detection; how AI algorithms can identify irregular account activities, helping protect individuals from potential scams. Furthermore, AI has revolutionized drug discovery, significantly reducing the time and cost involved in bringing new drugs to market.

To shed light on real-world applications of AI, Mark has compiled over 400 case studies, showcasing how companies in Ireland have utilized AI in their business. These examples demonstrate how technology can serve as an enabler, benefiting society in various domains.

Addressing concerns surrounding AI, Mark said it is essential to consider the role of regulation and the need for ethical considerations. The European Union has been proactive in establishing the AI Act, which sets criteria and limitations for AI products. Similar regulations are being implemented in different countries to ensure privacy and mitigate biases inherent in AI algorithms. Transparency and explainability are crucial factors in building trust in AI systems, as they address concerns about misinformation and manipulation.

One common worry regarding AI is the potential for job losses. While it is true that automation may lead to the automation of certain tasks, Mark highlighted that it is unlikely to result in complete job displacement. Studies suggest that between 10% and 50% of job roles may be automated, but humans will still play a vital role in overseeing and complementing automated processes. The evolution of AI and automation should be seen as an opportunity to redefine job roles and emphasize creativity and problem-solving skills. Upskilling and digital dexterity will be crucial to adapt to the changing landscape.

The conversation surrounding AI has gained momentum in the past few months with the rise of ChatGPT contributing to a broader national dialogue. The rapid advancements in AI technology, while promising, necessitate ongoing discussions and involvement from government. Building a future where AI is utilized for societal improvement requires collaboration, awareness, and responsible development.

As the field of education embraces AI and ChatGPT, Mark talked about how it opens up new possibilities for personalized learning experiences. While it is too early to determine if ChatGPT will replace Google, the capabilities of AI models like ChatGPT have shown great potential for transforming how we interact with technology. Personalized virtual assistants may become more prevalent, offering tailored journeys for tasks like cooking lessons, fitness advice or travel planning.

Misinformation remains a challenge in the era of AI, just as it does in social media. Mark highlighted how establishing fairness, transparency, and explainability in AI systems is crucial to combatting misinformation. The industry must prioritize building trust and ensuring that AI is perceived as a reliable and credible technology.

In conclusion, AI presents immense opportunities to enhance our lives across various domains. While concerns exist, ongoing efforts in regulation, ethics, and transparency are combatting these issues. By embracing AI responsibly, fostering education, and leveraging its potential, we can navigate the future with confidence, ease public concerns and unlock the benefits AI has to offer.