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The AI/ML Analyst Value-Add to the Business

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Today, risk-averse business processes can impede innovational opportunities. The systemic nature of today’s business processes creates limitations in understanding the desire and demands of today’s customers because of the unwillingness to increase the risk profile across the organization.

The role of an AI/ML analyst is critical in both pre-service and post-service contract operations. Since most business models today are constantly leveraging the market for value capture and value creation, they can be prone to generate increased risks to the firm’s operations (e.g., structure, processes, and assets).

For example, a telecommunications company today would look to assess AI/ML vendors while at the same time understanding the impact of disrupting current and traditional vendor and supplier management models. Because intelligent systems are omnipresent and encompass numerous environmental variables with degrees of pre-configured bias in machine learning models (e.g., Supply, Demand, Labor, and Social/Economics), these intelligent agents can aid in the early identification of emerging trends while augmenting employee decision-making.

A few example areas of AI/ML technology that a telecommunication’s company may be missing for increasing innovational and new market revenue opportunities:

  • Implementing Virtual Call Centers (Chat Bots, Virtual Agents) that remain deficient in solving for the customer issue.
  • Disruption to traditional advisory models (content creation using Brave rewards instead of the traditional McKinsey/Gartner sourcing models, and consulting frameworks, and the continued sunk costs in the monetization of Knowledge Capital).
  • Failure to identify the convergence of ML, Blockchain, 5G, and IoT (Smart Cities, Supply-Chain, Transparent Economic Modeling).
  • Overlooking the value generated from data mining in Shared Value Ecosystems (Platform Economics, Network Effect, Critical Mass).
  • The ambiguity from using systematic business processes from Natural Language Processing (NLP) and Customer Sentiment Analysis (CSA) that are counter-productive in creating competitive advantages and leading to missing critical new market opportunities earlier in the trending.

Differing Perspectives between Systems Engineers and AI Developers

Systems Engineers (SE’s):

  • SE’s generally align with existing business processes to provide an effective basis (from within the processes themselves) for systems procurement. 
  • SE’s best practices typically align with traditional sourcing model methods (e.g., best practices Vendor Management) that are often implemented by outside advisory and consulting firms.
  • SE’s working in traditional business processes force commitment early in the design phase that limits innovational opportunities that an AI/ML developer looks to identify and monitor throughout the length of the contract (e.g., SCRUM team sprints to meet project deadlines) established by the Project Management Office (PMO) and Vendor Management Office (VMO). 
  • SE’s objectives are to establish a clear relationship between process enhancement for specifications and designs.
  • SE’s are mostly concerned with checking for defects introduced during the building process with minimal focus on if the system is actually solving the user challenges.
  • SE’s assume the design to be correct because it is based on the specifications of the system.

AI Developers (AI DEV):

  • AI DEV addresses augmenting or enhancing the human element through the use of intelligent agents.  
  • AI DEV uses knowledge-intensive methods.
  • AI DEV is more concerned with software and domain integration than systems engineering processes and specifications.
  • AI DEV requires domain understanding to formulate ideas with users.
  • AI DEV will identify functional and non-functional requirements.
  • AI DEV will use abstract modeling to convert user requirements into technical specifications.
  • AI DEV will develop a requirements document to achieve consensus between the end-user and developers. 

AI/ML Analyst Value Add

The role of the AI/ML Analyst operates in tandem with the Vendor Management Office (VMO) while at the same time performing the Relationship Management attributes (common in best practices VMO organizations) with the AI/ML vendors constantly measuring against expected service, value maximization, and budget controls.

The AI/ML Analyst can solve for:

  • Leveraging risk in current IT/Business Processes that are entrenched in today’s ecosystems.  
  • Provide synthesis and communication between systematic business process models and AI/ML enhancements while reducing friction in today’s business ecosystems.
  • Aid in the early identification of new market opportunities and prevent innovation stalls.
  • Assess and remedy business process risks that limit the exposure to new market opportunities.
  • Monitor costs against benchmarks using best practices and business intelligence. 

5-examples of AI/ML Analyst Due-Diligence should perform for AI/ML Vendors

  1. How are disruptive strategies affecting the company’s top clients? Consulting revenue depends on client prosperity, and meeting investor obligations.
  2. How does the company prevent knowledge loss? AI/ML vendors depend heavily on the intellectual capital of employees, yet some companies face high levels of voluntary attrition, and with them, account knowledge.
  3. How dependent is the firm on a dominant customer? Some vendors rely heavily on one or two key clients; the non-diversification can lead to increased risks if a key client should terminate the agreement.
  4. How many projects does the firm have on the books? The backlog is an important predictor of future cash flow but also means susceptibility to not applying the finishing touches.
  5. How many professionals and administrative staff follow the ethical standards for developers? Understanding the division of skill sets in your supplier ensures quality and reductions in agent bias.

Reference list

https://www.linkedin.com/pulse/aiml-analyst-value-add-business-sean-halverson-/

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Business books to read in 2021: top picks

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Business books to read in 2021: top picks

The COVID pandemic has changed habits and reassigned priorities for all of us. There is, however, a segment of people whose natural way to treat crisis is to use the opportunities it offers: the entrepreneurs.

With an unprecedented economy stimulus coming from the U.S. Federal Reserve, the idea of starting new business (or investing in an existing one) became even more popular than previously. This, however, requires a certain level of preparation: you definitely don’t want to learn on your own mistakes losing money. Thankfully, business and entrepreneurship is the field where there are tons of useful and inspiring books to learn from.

But how to navigate through those thousands of books and authors? Let’s make an overview of the most in-demand business ebooks as of 2021.

Finance and Investments

Business books to read in 2021: top picks

Strongly recommended is “The Intelligent Investor” by Benjamin Graham, an eminent economist and investor of the 20th century. He has created a guide that has inspired millions of people around the world for 70 years. Since its first publication in 1949, the book has become a veritable bible of the stock market. The modern edition is supplemented by comments by financial journalist Jason Zweig, who draws parallels between Graham’s examples and modern realities, and also provides a deeper understanding of how to adapt the author’s philosophy to everyday life.

Internet Technology

The ITIL (Information Technology Infrastructure Library) is a framework for standardizing the selection, planning, provision, maintenance and the entire life cycle of IT services in a company. The goal is to improve efficiency and achieve predictable service delivery. 

The ITIL books cover key concepts of service management, the four dimensions of service management, the ITIL service value system, and ITIL management practices.

Entrepreneurship

This is an extremely wide field of study, incorporating both motivational, inspiring books with those designed to improve hard skills. As for the first option, the “Money: Master the Game” by Tony Robbins keeps first place in our wish list.

Another must-read is “Think and grow rich” by Napoleon Hill. This bestseller was written in the end of the 20th century and has been reprinted over 40 times. In his book, the author has collected the stories of famous millionaires of his time who stubbornly went towards their goals.

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What is The Full Form of PhD?

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The full form of PhD is a Doctor of Philosophy or a Doctorate in Philosophy.

This is a postgraduate academic degree awarded to individuals who have gone through the process of studying and researching extensive subject matter in their field. It can be obtained from an accredited university and requires one to go through a research dissertation.

What Is The Meaning Of PHD?

PhD is a doctoral degree that takes the form of a research degree. It generally recommends a substantial amount of independent, original research and a formal defence of that research.

The word “Doctor” in the abbreviation PhD comes from Latin “doctor” which means “teacher”. In other words, PhD holders are teachers who have done extensive teaching and research as demonstrated by their dissertation.

What Is The Abbreviation Of Doctorate of Philosophy?

PhD is the abbreviation for Doctorate of Philosophy.

Doctorate of Philosophy is a postgraduate degree that requires three to five years of study and research. The abbreviation for Doctorate of Philosophy is PhD.

Which is higher MD or PhD?

A person can be awarded with a Master of Science degree (MS) after completing course work and passing a series of written and oral exams. Master’s degrees typically take one to three years to complete.

A PhD is a Doctoral Degree, which is the highest academic award in most countries. To earn a PhD in the US, students usually have to complete at least four years of study beyond an undergraduate degree.

Master’s degrees are often seen as higher than Doctoral Degrees because they require more advanced subject knowledge and coursework.

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NEW from Apple

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We weren’t the only ones streaming the party yesterday. Apple held its latest event — the one that annually triggers iOS users to stop and think, “Hm, do I need an upgrade?”

Mobile gamers, in particular, could be tempted by the new iPhone 13 Pro and Pro Max, which got the new A15 Bionic chip. Apple said it’s the “fastest CPU in any smartphone” with a 6-core CPU (one more than the new non-Pro models). Because of the updates, the Pro models allow for 50% faster graphics and can last about 1.5-2.5 hours longer than the iPhone 12 Pro and Max models, respectively.

Apple unveiling a new iPhone with a better camera is a free space on your bingo card every year. With this update, Pro models got a bigger, 77 mm telephoto lens (these help you to take photos of subjects that are farther away) with night mode and 3x optical zoom (up from 2x-2.5x). Users also get new wide and ultrawide cameras, autofocus, and a new mode for taking close-ups up to 2cm away.

The standard iPhone 13 and Mini models also feature the A15 Bionic chip. The dual camera got updates as well, but Apple is mostly playing up its new Cinematic Mode across all models. It’s basically portrait mode but for video.

Apple Watch Series 7 also got some upgrades, most notably a wider screen and 20% larger display.

NEW from Apple

The biggest star of the show though was probably the iPad — specifically the new iPad Mini. It got the A15 Bionic chip and lost its home button — meaning it now looks like a mini iPad Air complete with a USB-C port and Touch ID on the power button. The iPad and iPad Mini also got ultrawide cameras with Center Stage. The feature uses machine learning to adjust the front-facing camera during FaceTime video calls to keep you in frame.

We’re looking forward to hearing what you’re most excited about and what you’re disappointed by — you too, Android users.

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