Are businesses well prepared for an AI-driven future?

In conversation with Abboud Ghanem, Regional Vice President, Middle East and Africa, Alteryx.
1. As one of the top technology solution providers globally, where do you see AI in GCC when compared to AI across the globe?

Although the current ability of AI can be overestimated, companies across GCC are starting to recognize the potential of machine learning (ML) and artificial intelligence (AI). Global technology research firm International Data Corporation (IDC) have forecast Artificial intelligence (AI) spending in the Middle East and Africa (MEA) is poised to reach $290 million this year, rising to $530 million in 2022.

However, few companies have been able to successfully implement and deploy this new technology alongside business strategy.

It is expected that investment in AI across the region will grow 42.5% year on year in 2019 and continue increasing at a compound annual growth rate (CAGR) of 22.2% over the 2019-2022 period. According to Gartner, only 46% of CIOs have developed plans to deploy AI, and ultimately only 4% have made the concept a reality.

2. With appointing an AI Minister, UAE has shown that it is thinking way beyond most of the countries in the world, how does Alteryx compliment UAE's AI Vision?

With data forming the bedrock upon which Dubai's Smart City initiatives are built and the advance of government-backed technology programs, we are seeing a surge of interest in advanced data analytics within the GCC. Organizations such as the Abu Dhabi Islamic Bank, Al Futtaim Private Company and Dubai Electricity, and Water Authority in the UAE (DEWA) are already gaining knowledge from data by enabling data producers to analyse for insights and make data-driven decisions.

This acceleration of AI and ML capabilities are helping to accelerate the time-to-insight and breaking the barriers of what is possible. But while AI may be becoming the popular dream of data analytics, companies need to keep focus on the humans in the loop.

We continue to make the Alteryx Platform easier to use for data analysts, while extending its ability to handle more sophisticated data science outcomes for the trained data statisticians, driving an increasing number and variety of use cases in most every industry and functional area of the enterprise.

With the recent introduction of Assisted Modeling, Alteryx amplifies the capabilities of analysts and citizen data scientists, delivering "explainable artificial intelligence (AI)" in a code-free environment. Recognizing the pervasive talent gap that exists between data scientists and data workers in the line of business, Assisted Modeling helps teach data science with a guided walk-through and aims to help all data workers, regardless of technical acumen, advance their skill sets in the process of building machine learning models.

Our approach in building Assisted Modeling is to advance the skills of the data worker, creating next-level citizen data scientists capable of building the machine learning models required to tackle the advanced analytic challenges of the future. Assisted Modeling provides users the transparency and control needed to build trustworthy machine learning models that drive business outcomes without writing a line of code.

As an output of the application, users can access code-free machine learning tools directly within the Alteryx Designer interface. Assisted Modeling allows any data worker to construct machine learning models, understand how and why their models work, and capture modeling decisions, turning raw data into informed business decisions with unprecedented speed and confidence.

3. Which are the top 3 industries where you see AI making a bigger impact?

Industry-wise, IDC's research states the top three industries in terms of AI investment in 2019 will be banking, manufacturing, and retail.

4. What according to you is the understanding about the impact of AI amongs C-suite leaders in the region?

The biggest challenge facing any company today is surviving the half-life. In the case of our customers, this means driving successful business transformation and recognizing data as the lifeblood. Many senior leaders from organisations across the world are trying to tackle bringing the data assets they have to life in order to gain critical business insights and make better data-driven decisions. This smart approach to data now will help guide the way for a successful AI-driven future.

5. If you had to list one example of how you helped a client with their AI strategy and how it helped their business, which one would it be?

AI and ML fit into the analytical process in three ways. First, descriptive analytics, which states what has happened. Second, predictive analytics, which says what could happen or why something happened, and finally prescriptive analytics, which gives recommendations for action.

More than half of our current customer base of nearly 5,300 customers in 80 countries, including 33% of the Global 2000 have deployed the Alteryx platform to help build predictive models, an essential element of the machine learning piece of AI.

There are applications in every industry. Coca-Cola uses Alteryx to help restaurants predict how much soda to order. Airlines use it to hedge the price of jet fuel. Banks use it to model derivatives. Royal Dutch Shell PLC leverages advanced data analytics to monitor operations and improve its supply chain decisions and inventory. Working alongside AI, Shell use predictive analytics to predict when equipment will fail. Allowing Shell to step in and fix it before it breaks. Spending less time on complex data interpretation while preventing unplanned downtime of its assets, which boosts efficiency and lowers costs.

6. While we know AI will increase efficiency and productivity, what will the cost implication and its impact on jobs be?

AI will bring massive changes to work, life, and play, impacting everyone's lives. Although these impacts are likely to be most dramatic within business, the existence and rapid growth of AI technology cannot, and should not, threaten a human's ability to tackle the world's greatest challenges and answer the most complex questions. It can only enhance it.

If you demystify them fully, A.I. and ML are just maths. It all comes down to maths and the fundamental principle of machine learning for supervised learning which is where you give it a label set of data and you get you ask it to try and reduce the error in its predictions as much as possible. That's all it is that's all A.I. is ever going to be.

Hence it needs to be trained on some form data before being set loose and asked to predict based on the model that it's built from that trained data. And as humans, if we don't set up that trained data correctly then this is one of the pitfalls of AI, you end up with bias in your data and you end up with a model that's just not going be as effective as it could be, or it may maybe your competitors have.

Yet, without the right workforce, organisations simply cannot proceed to tackle the technical challenges existing in a data-driven industry and reverse the inconsistencies and set-backs associated with data-led AI projects.

7. We have seen the technology leaders like Mark Zuckerberg and Elon Musk divided over their views on AI, so is it a boon or a curse to humanity?

A common fear that resonates within the population when artificial intelligence is discussed, is that it is going to take away jobs. It is no surprise that this is their reaction when headlines such as 'Robots and artificial intelligence will take over HALF of all tasks in the workplace by 2025' are plastered across the news.

The truth is that it will take years before many organizations realize the true potential of AI and ML, but it is never too early to lay the groundwork now for an AI-driven future.

However, it is possible for humans and AI to live in harmony, in fact, humans will always hold an important role within the development of AI.

But without the talent, organisations simply cannot proceed with the technical challenges ahead and reverse the slowdown of data-led AI projects. In fact, if an organization is not already thinking about what an AI strategy looks like, its competition is likely one step ahead. There's no time to waste.

8. We see a lot of organizations talking about a technology driven future but fail to execute their plans, what would you like to suggest to them?

The important points to consider when getting started with technologies such as AI and ML are:

Ask the right questions. There are four things organizations need to be thinking about when it comes to a future-proof data strategy. What data is available within the walls of my organization? What data do we need to acquire externally to drive differentiation? Is our data available in a way that can be readily available for machine learning and AI? And perhaps most importantly - where can we upskill our line-of-business, what requires pure data science and AI know-how and what can IT manage? The answer to these questions should serve as the foundation to your strategy.

Take a multi-year approach. Successful AI/ML implementation does not happen overnight. The smartest organizations take a multi-year approach to data acquisition and strategy, focused on compiling data from different sources and silos-often built around a Center of Excellence (CoE)-and investing in the right technologies and people to lay the foundation. At the same time, these organizations look to cloud-based offerings from companies like Amazon, Microsoft and others to create intermediate data storage that can support diverse use cases as strategies progress over time.

Always put humans at the center of the strategy. A recent study from ZipRecruiter found that "the most successful applications of AI have been when used in partnership with humans, rather than as a replacement." That's why, according to the study, AI has created three times as many jobs as it killed last year-and companies are continuing to invest in talent with data skills despite the advancement of automation technologies. The World Economic Forum predicts that data-related jobs will be the most in demand within the next four to five years, along with AI and ML specialists.

Build a multidisciplinary team. A diverse team that incorporates AI experts, data scientists and line-of-business analysts presents a more holistic approach to AI/ML, as the overall project encompasses the data collection process all the way to the data mining activities, machine learning and automation. Those who are able to engage with the data gathering, processing and training will be able to optimize their contribution to their organizations, and seriously enhance their individual or corporate ability to achieve goals.

Bridge the skills gaps. There is increased demand for any data worker, regardless of technical acumen, to do more with data, and organizations need to look for ways to up-level skillsets, build models in understandable and transparent ways and generally bridge the skills gaps across the organization. Since AI data design requires "data speak" to help build workflows, organizations must implement technologies such as augmented analytics that automate data prep, insight discovery and data science (i.e. autoML) all while communicating actions to roles with less AI know-how.

9. What are your top 5 predictions for AI in the GCC within the next 5 years?

Big data, artificial intelligence, machine learning, and predictive and prescriptive analytics are all the buzz. Everyone's talking about the incredible potential of these technologies and will continue to do so for years to come.  From non-human pattern recognition and intelligence results, machine learning for diagnosis and treatment planning and AI face recognition helping locate missing people, it's clear that AI and ML will undoubtedly shake up the business world and life as we know it for years to come.

But generating real value from AI is nearly impossible if you don't have the right organizational and strategic infrastructure. Organizations need to empower each and every human member of their business to be thinking about how to leverage the technology. No matter how AI and ML evolves, data will always be at the forefront and one of the most important drivers of success and true digital disruption.

10. What can delegates expect from your presentation at the Artificial Intelligence Forum in September?

Delegates will be able to see how we are revolutionizing business through data science and analytics by empowering every data producer, regardless of technical acumen, to transform their data into actionable insights faster than they ever thought possible and improve their business.  They will get to experience how our customers enjoy the thrill of solving through the Alteryx platform, enabling users of all kinds to work the way they want to work, and change their organisation's business like never before.

• Dubai