Artificial Intelligence and Emerging Digital Technologies
We could not talk about the future without mentioning our past. I tell it because all currently artificial intelligence impact doesn’t start in 2022. It has become a long journey since the year’s 50, the magic turns reality because of the combination of big data and cloud computing availability. More data to train algorithms and scalable infrastructure to process them. Clarification number two, generative ai is just a combination of probabilistic algorithms, called transformers, because the use of neural network architecture transforms or changes an input sequence into an output sequence. No magic, once again.
I believe at the end of 2024, most people finally understand the generative ai is just one more tool to optimize humans on repetitive and massive activities, build of mathematical methods. But now, people recognize that emerging technology has two sides, the good: it really demonstrates efficiency and productivity when applied for its main capacity (text oriented). But, to process substantial amounts of data and return assertive answers, you will have a large cost enrolled (FM tokens, data, people training, etc).
McKinsey Global Institute’s research, estimates that generative AI will add between $2.6 and $4.4 trillion in annual value to the global economy, increasing the economic impact of AI by 15 to 40%. American bank, Goldman Sachs predicts a 7% increase in global GDP attributable to generative AI.
Generative Artificial Intelligence projects are not just LLM model’s tokens[1] fees. To build an application with generative AI embedded you’ll need an infrastructure (Cloud services, GPUs), Data (structured and no structured data), human resources (multidisciplinary teams) and various LLMs to test.
Gartner’s research in July of 2024, outlined concerns around the future of generative AI projects. The significant upfront investment and recurring costs, as seen in the below graphic, at least 30% of GenAI projects will being abandoned after proof of concept by the end of 2025:
Given this scenario, what do to extract the best from generative AI and obtain sufficient financial results to compensate for recurring and continuous investments?
I will list 8 steps to consider on your generative ai strategical journey:
1- Identify the use case what really means one issue or a large opportunity for your business. And remember, generative artificial intelligence main features are:
· Text generator was trained on large datasets of text content and use natural language processing (NLP) to interpret the text.
· Image AI model was training with data from labeled images and uses generative adversarial networks (GANs) or diffusion to generate images.
· You could combine descriptive artificial intelligence with generative artificial intelligence to create your best solution.
2- Generative AI excels in multiple scenarios and can greatly reduce time for repetitive tasks.
3- Review your currently process, understand where and how you could optimize that applying generative ai.
4- Enroll all stakeholders and users on assessment journey. A multidisciplinary team could better understand and explore better ways to solve risks and issues.
5- Just after having a clear understanding of your use case, design your technical architecture.
6- Calculate the “Return Of Investments” (R.O.I.). For artificial intelligence projects that could be a little beet difficult than for ERP projects for example but isn’t impossible. For generative AI, you need to consider the cost of implementing, what enroll infrastructure (cloud services or on-premises), data availability (buy external data, internal data treatment), people training, security, risk management (privacy laws) and the expected benefits. The benefits could be cost savings, revenue growth, and other measurable gains.
7- Don’t forget artificial intelligence’s projects never end. You must think about the continuous training models to keep them always assertive. That means, recurrent costs to research and curator.
8- Finaly, you must establish an AI Program to support your solution alive. That program involves the development of a set of AI policies or AI Governance to have the responsible use of artificial intelligence. You could create a center of excellence, with a multidisciplinary team what would be responsible for spreading the new culture around the organization.
The new digital technologies as the super-apps, IoTs, augmented reality and others with generative artificial intelligence embedded in, could open new opportunities for many economic sectors as education, health, agriculture, transportation, communications, arts, sports, public services, and others. Now technology is not the responsibility of one department, all professionals need to know where and how to better use technology.
Now more than ever, collaboration and idea-sharing are essential. While artificial intelligence handles repetitive tasks, critical thinking and life experiences remain uniquely human.
References:
McKinsey — The State of AI in 2023: Generative AI breackout year — (https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2023-generative-ais-breakout-year)
Gartner Emerging Tech Impact Radar: Generative AI( https://www.outsystems.com/1/gartner-report-generative-ai/?utm_source=google&utm_medium=search-ads&utm_campaign=GOOGLE_SEARCH_NB_AMER_LATAM&utm_term=gartner%20generative%20ai&utm_adid=gartner_ai&utm_campaignteam=digital-mktg&utm_partner=none&gad_source=1&gclid=Cj0KCQjwm5e5BhCWARIsANwm06iPK-zKKQ84glorPHHHskynWZNgWmpO8HzBRXE6TZo31n18Yl4vSq8aAkJhEALw_wcB)
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