Navigating the possibilities of AI-enabled tech

As I was finishing my studies and preparing to enter the workforce, I wanted a job through which I could immediately have responsibility and the ability to make a real difference. I also wanted to work for an organization where I would continue to learn. McKinsey fit the bill, offering challenging work I could own and the training and mentorship to help me keep growing in my field.

I joined the firm in Moscow as an associate after completing my master’s in CEMS at St. Petersburg State University. About four years later, I left to earn my MBA sponsored by McKinsey at Columbia Business School. When I graduated, I didn’t come back to the firm right away. Instead, I joined an internal consulting team at a Danish pharma company. I wanted to work on the client side and get a new experience to help me as a consultant. I was in that role about a year-and-a-half before rejoining McKinsey in Copenhagen. The desire to use cutting-edge technology to solve real-life problems for our clients was a major factor that drew me back to the firm.

In total, I’ve been with McKinsey for five years, and I now serve as an engagement manager in Copenhagen.

A snapshot of what I do

As an engagement manager, I am responsible for a project from start to finish, including helping teammates run analyses and deliver our final products to clients. I work in a range of functions and have begun to focus on healthcare and pharmaceutical industries.

Understanding game-changing tech 

McKinsey aims to stay a step ahead of emerging tech. Right now, the firm has a strong interest in Software 2.0 because of its tremendous implications for clients across verticals, including automotive, financial services, and entertainment.

With Software 2.0, programmers no longer need to build software by writing and repeating sections of code. Instead, neural networks use machine learning to span a search within a possible program space to test, iterate, and identify the most efficient program to reach a given goal.

The technology promises to reduce many of the difficulties and complexities that hinder the development and application of artificial intelligence models. It is game-changing because organizations can use it to quickly build, train, manage, and scale software and new AI applications.

My role in supporting McKinsey’s Technology Council expands beyond Software 2.0 to look at other trends in AI-enabled technologies and the impact on different industries, including pharma. We are looking at underlying enabling technologies used together, for example, classic machine learning, deep learning, and quantum hardware, and applied technologies like computer vision, IoT, and Software 2.0.

Forecasting technological shifts

My goal is to understand and quantify these technology trends by looking at many indicators, including patent filings, scientific publications, investments, and number of startups in the space. This analysis helps us understand which technologies are accelerating or slowing down. We also evaluate where we see the most practical applications of emerging technologies.

We believe Software 2.0 is poised to offer a next-generation customer experience, providing new ways to interact through digital channels and tailoring products based on preferences and analytics.

There could be great advances with algorithms and advanced technology applications helping solve complex problems, from pharma drug discovery methods to pricing and financial risk prevention. Additionally, a growing set of solutions could reduce or eliminate human intervention in everyday processes and field applications, from warehouse logistics to precision surgery.

The possibilities feel limitless, and it’s exciting we can give our clients an edge by understanding these technologies.

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About Anastasia

Anastasia is a mother of two, who is active in the Parents at McKinsey and Copenhagen Women Community groups. She loves to read and spends as much time as she can sailing.

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