On Part 1 we appreciated the evolution of data to present form—and predicting the future.

We may need a recap. We started with types of data (written , audio and visuals) and the tools or earlier machinery in use—such as printing presses and typewriters for written data.

We did not cover  telecommunication (Radios, Televisions, and Satellite TVs). But there was evolution going alongside data evolution.

MaTools Edu: Printing presses, Typewriters, Radio and Television.

Shanduko Yekutanga(1): Computers, Advanced Printing Presses, Online Radios, and thers

Shanduko Yechipiri (2): Internet yakashandura Data transmission, Data creation, Data Storage, Data Editing. Internet ikaunza E-commerce nezvimwewo zvakawanda.

Shanduko Yechitatu (3): Smartphone accelerated Data collection. Makomo nemakomo e data akazara with billions of citizens creating content and Social Media helped in the revolution.

Shanduko Yechina (4): Toitei nemakomo makomo e data rauya iri? Nezuro takati I duri. Duri ririkufashukira ne data, rimwe richingoramba richiuya kasingapere.

Ma Problems aivepo

Intellectual Property Rights: Google inova iyo yakazarisa kukunda vamwe vese—kwakatanga kuita maproblems ekuti vene vedata vainge voti tinodamuripo. Haungashandise maphotoangu, haungashandise data rangu.

Kugadzira: Hawaikwanisa kugadzira ako maphoto, kugadzira music, kugadzira mafilms nezvakawanda. Hongu waigona kuenda kunaana Canva, nemamwewo ma websites.

Kutuma: Hawaikwanisa kutuma Google kuti pindura ma clients, vabatsire zvinovashupa. Kudata—hawaikwanisa zvirinyore kuti ndipe summary yenyaya iyi. Therefore Kutumika kuti ikushandire raive dambudziko gurusa.

Kuuya kwe Artificial Intelligence

Yakauya kuzogadzirisa maproblems ese aripamusoro apa—Hatina kuadoma ese nekuti mazhinji.  Kana kwaane ma Agents anotumika uye achiita mabasa nekukurumidza. Uyezve achikwanisa kuzvifungira hupenyu hunotirerukira.

Saka ndeapi maproblems achafanirwa kugadzirwa atichiinawo?

Ruzivo: Hongu zvidzidzo zviriko. Hongu munhu wese oziva kuti kune AI. Asi ruzivo rwuchirwudukusa. Asi ichasvika nguva yekuti munhu wese anenge avemo.

Vashomanene: Varikushandisa vachivashoma. Vane hunyanzi vagova vashoma zvekare.

Infrastructure: Infrastructure ichiri diki—asi investment irikuzara chaizvo fanike nyika dzekumavirira.

Resistance to Change: Kubva kuma type writer kuenda kuma computer yakatova hondo tsvuku. Kubva kuma landline phones kugamuchira macellphones hazvina kuva nyore.

Conclusion

Liberalization: Data raiva ne a selected few vaiita capture, create, use and share. Internet ne smartphones yakaunza billions through Social Media kuti tiite murambamhuru pakuzadza dura redata.

Kutumika: Data ravekufanira kutishandira using AI Tools. Chichatanga kutumika as first stage(Hatisati parizvino tave ne perfect efficiency asi tichasvika)—Second stage kuzvifungira roita rega. Parizvino tichavanemakore vanhu vachituma macomputers. Asimberikwazvo macomputers ngaazvifungire opedza basa. Gadzira album re Sungura—wogadzirazve nema videos. Wotengesa wondipa mari.

Part 3 ndiyo ichave final—tichatarisa maopportunities kubva kuma type writers kusvika AI Revolution.

Tinotenda nekuverenga kwenyu.

Don’t miss the Digital Marketing Lessons we will be offering in June 2026

The last time we looked at the top risks in the world was in 2012 where unemployment was ranked as the top risk across the globe. And our analysis unleashed a forum concept called Business 2 Entrepreneur (B2E). If you structured your business model to cater for entrepreneurship needs—then the sustainability of your business was guaranteed. We cited Innscor, Delta, Varun, The Chinese, Shipping and Logistics (Runners), Mukuru, Ecocash, Irvines Chickens and more.

And Delta has just entered the billion dollar revenue threshold in recent times. The B2E model should be part of finance studies for those interested in appreciating local conditions.

Anyway we look at the latest report from WEF and what are we picking?

Geo-economic Conditions already playing out in South Africa and likely to impact the rest of SADC and the continent at large. And this will trigger more social complications across the region.

Is the region ready for possible (if not imminent) voluntary and involuntary migration? Extreme weather conditions and pollution also listed and closely interlinked too.

And the present challenges not going away but carried over into long term with 50% of future risks aligned to environmental conditions.

Will Kariba Dam still hold sufficient water for Hydropower by 2036? The adverse impact of AI to exacerbate environmental conditions.  

So what opportunities do you see from this?

• Invest in Green Energy—ordinarily no need to repeat this as its now common knowledge. However we repeat for emphasis. Build your brands and be at the top in Green Energy. This includes adopting new technology as part of your long term strategy. Benchmark your performances to the best across the globe.
• Invest in land—This is already happening in Zimbabwe with cluster homes, Sabhuku deals, Econet strategic positioning through Infraco. The rise of REITs in Zimbabwe. Just get land or invest in real estate disruptions.
• Invest in AI—Interestingly Artificial Intelligence impacts every facet of life creating new opportunities and risks. But highlight AI into Green Energy, Land and Society.

The disruptions to impact business opportunities and we are already in transition. By 2036 crypto currencies could be dominating, and most of what is coming can be gleaned from developed economies. What is however surprising is the mention of Health. Is it because most of the analysts come from financial backgrounds? Only time will tell.