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In the ever-evolving landscape of complex technology, TM Forum, the Telecoms Industry standards body, stands out as a pioneering force in leveraging artificial intelligence (AI) to drive innovation and operational efficiency in an enterprise. This paper delves into how TM Forum suggests an approach to strategically apply AI, to scale applications, and maintains robust governance processes to ensure responsible and impactful use of this transformative technology within the Telecom domain and further afield.

The Strategic Use Of AI

TM Forum has long recognised the transformative potential of AI. According to Professor Paul Morrissey, Global Ambassador for AI at TM Forum, “AI has been an essential capability for Telco for years now, and we see it only increasing in importance and impact.” The organisation looks to provide Best Practice for the seamless integrated AI into its Telco core operations, enhancing both the security and personalisation of services.

One of the primary ways TM Forum promotes AI is through its decision management platform, which serves as the AI brain running within network. These recommendations enables the company to make real-time, complex decisions on transactions, and decisions significantly enhancing customer experience, network continuity, fraud detection and prevention to highlight just a few operational areas.

Choosing The Right AI Applications

The strategic application of AI at TM Forum is not a matter of chance but a result of a meticulous decision-making process. The Forum recommends a two-tiered review mechanism to evaluate AI opportunities: an AI Canvas (IG1028) and a subsequent deep technical review.

The AI Canvas recommends a series of examinations to asses the Business Value of the Use Case and consists of experts from various domains, including legal, privacy, product, and business (the assessment board). This board assesses the intent, data provenance, and ethical implications of potential AI projects. Morrissey explains “We start with problem definition then move through legal, privacy, product, business intent, and that is really important to understand—what are we trying to do here? Should you, do it? Can you, do it?”

Once a project passes the initial review, it undergoes a rigorous technical evaluation. This involves assessing the scalability, ROI, and operational efficiency of the proposed AI application. “If it doesn’t scale, it doesn’t matter,”

Scaling AI Across The Organisation

This approach to scaling AI involves silent mode validation, where new AI techniques are tested in parallel with existing systems. This method allows the organisation to measure the impact and efficacy of AI without disrupting current operations.

“You should run this in production in parallel with what we already have and then decide if the delta is worth the additional expense.

To ensure that AI initiatives can be effectively scaled, TM Forum recommends that organisations invest heavily in training and upskilling their workforce. The establishment of specialised workbenches for different roles, such as software engineering, data science, and sales, to provide tailored AI tools and training. Asking the question, what’s the right level of investment in data science, engineering workbench, generative and otherwise? How do you tailor it to your environment?

Governance And Ethical Considerations

Governance plays a crucial role in any organisations AI strategy. The organisation should implement a comprehensive AI governance framework to oversee the ethical and responsible use of AI. This framework should include continuous monitoring, compensating controls, and feedback loops to ensure ongoing model efficacy and to mitigate unintended consequences (AIOps).

Any organisation’s governance processes should ensure that all AI applications align with its core principles and regulatory requirements. This involves regular reviews and updates to its AI models to address concept drift and other challenges that may arise over time.

Looking Ahead: The Future of AI

TM Forum continues to explore new AI technologies and their potential applications. Morrissey discussed the impact of generative AI and quantum computing on an organisation’s future strategies. “We are looking at quantum computing both from a security perspective and as a means to solve complex combinatorial problems that are beyond the reach of classical computing.”

This forward-thinking approach ensures that TM Forum remains at the forefront of technological innovation while maintaining the trust and confidence of its members. The strategic use of AI not only enhances its current operations but also positions it to tackle future challenges and opportunities in the technology sector.

The strategic application of AI serves as a powerful example for its member organisations looking to harness the potential of this technology. Through a well-defined governance framework, rigorous review processes, and a commitment to ethical practices, TM Forum try’s to ensures that its AI initiatives deliver significant value while upholding the highest standards of responsibility and integrity. As AI continues to evolve, TM Forum’s proactive and strategic approach will undoubtedly keep it at the cutting edge of innovation in the Telecoms industry.

Yesterday marked the beginning of a new chapter in my life. As I lay down for my first radiotherapy session for prostate cancer, I was introduced to ‘Juniper’, the state-of-the-art radiotherapy machine. Over the next 20 days, Juniper and I will be spending fifteen minutes a day together, getting to know each other intimately. Although this journey was born out of a medical necessity, I’m taking it as an opportunity to bond with this magnificent piece of technology.

It’s not often that you get to befriend a machine, especially one so crucial to your health.

Each session with Juniper is filled with a mixture of apprehension, hope, and wonder. The humming, the lights, and the meticulous precision of this machine have me marvelling at human ingenuity. And yet, I can’t help but wonder about the role Artificial Intelligence (AI) has played in Juniper’s design and operation.

AI’s footprint in the medical world is undeniable. From predictive diagnostics to robotic surgeries, AI has transformed the landscape of healthcare. It assists doctors in detecting anomalies in scans, provides personalized treatment recommendations, and even automates routine tasks. As I lie there, letting Juniper do its work, I contemplate how much of its operation is powered by AI. How does it precisely target the cancer cells while preserving the surrounding healthy tissue? How does it adjust to the slightest movements to ensure accuracy? Behind all these tasks, I suspect, lies a complex web of algorithms and data-driven insights.

Over the next few weeks, I plan to dive deeper into understanding the history and mechanics behind Juniper. This will not only be a therapeutic endeavour to distract from the physical treatment but also a cognitive exploration into the technological advancements that are helping people like me fight cancer.

In this journey, Juniper is not just a machine, but a beacon of hope, a testament to human progress, and an ally in my battle against cancer. As we proceed on this 20-day adventure, I promise to share more insights, anecdotes, and revelations about my new friend and the incredible world of AI in healthcare.

Stay tuned for more updates on this evolving story!

In the dynamic field of technology, Artificial Intelligence (AI) represents a notable duality, embodying a catalyst for operational enhancement while also serving as a conduit for various associated risks. Particularly, when considering the amalgamation of third-party AI products into organizational frameworks, a rigorous exploration and understanding of both the opportunities and the inherent dangers is crucial, a true double-edged sword.

Notably, among the quagmire of risks, the threat of inheriting biases from third-party AI products stands starkly, injecting a series of ethical and operational challenges that organisations must navigate. Integrating an external AI system without a comprehensive audit of its underlying algorithms and data can inadvertently embed inherited biases into an organization’s operations, thereby not only skewing decision-making but also potentially engender ethical discrepancies and reputational damage.

Consequently, the dichotomy of AI’s promising opportunities and the imperative to mitigate and manage its risks, especially those rooted in pre-existing biases, forms a complex but vital landscape that organizations must astutely traverse.

Opportunities Galore

Let’s explore the brighter side first: the opportunities.

• Operational Efficiency: AI simplifies complex processes, enhancing operational efficiency. It can analyse data at astonishing speeds, deriving insights that can help in better decision-making, be it in human resources, supply chain, customer service, or strategic planning.
• Cost Reduction: Over time, AI can substantially reduce operational costs. Automated processes and improved decision-making algorithms can optimize resource allocation, thereby curtailing unnecessary expenditures.
• Enhanced Customer Experience: AI excels in personalizing customer experiences. From chatbots that provide immediate customer service to predictive analytics that refine product recommendations, AI can uplift the customer journey to new heights.
• Data-Driven Decisions: Third-party AI systems, with their pre-learned patterns and capabilities, can be leveraged to churn out data-driven decisions swiftly, an aspect that’s quintessential in this age of dynamic market fluctuations.

However, it is imperative to note that sailing through the AI ocean isn’t without its tempests.

Unveiling the Risks

• Data Security: One of the paramount concerns of utilizing third-party AI is data security. External products may pose risks related to data breaches and compliance violations, especially if the third-party product doesn’t adhere to the security protocols adherent to your organizational and legal norms.
• Biases and Ethical Concerns: Your organization becomes susceptible to any biases or ethical misalignments that the third-party AI system might bring along. This could potentially tarnish the brand image and lead to inadvertent unfair practices.
• Dependency: Reliance on external AI solutions may make the organization vulnerable to the product’s future developments, pricing policies, and even potential discontinuation.
• Lack of Customization: Third-party solutions might not be entirely in sync with your organizational needs, limiting the effectiveness and perhaps even necessitating additional investments for customization or supplementary solutions.

Incorporating a Holistic Approach

The journey of integrating AI, particularly third-party products, should be embarked upon with a meticulously crafted strategy. Here, past experiences advocate for a balanced and mindful approach.

• Thorough Vet: Prior to integration, an exhaustive vetting process of the third-party AI product must be undertaken, scrutinizing its security protocols, ethical alignment, and long-term viability.
• Continual Oversight: The engagement doesn’t culminate at integration. A continuous oversight mechanism, analysing the AI’s performance, ethical implications, and data management, should be embedded in the operational workflow.
• Establishing Ethical Frameworks: An ethical framework must be conceived and adhered to, ensuring that the AI system aligns with organizational and societal norms, thereby safeguarding against biases and promoting fair practices.
• Scalability and Evolution: Choosing AI systems that are scalable and can evolve with the technological landscape ensures that the investment remains fruitful in the long run.

In light of all the above reflections, while AI, particularly third-party products, beckons organizations with its scintillating advantages, it is the incorporation of a meticulous, ethically grounded, and foresighted strategy that will pave the way for sustainable, equitable, and profitable futures. It’s not just about adopting technology but about adopting it wisely and ethically, ensuring that its ripples positively impact the organization and its stakeholders, now and into the future. At TM Forum we have developed a methodology do this as part of the examination of each individual AI Use Case through the AI Canvas.